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- Amazon ec2 not working when accessing through public IP - Stack Overflow
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- AWS Command Line Interface
- AWS Developer Forums: Python Development
- AWS Security Credentials - Amazon Web Services
- Basic Vim commands - For getting started (Example)
- chmod - File security
- Configuring the AWS CLI - AWS Command Line Interface
- Connecting to Your Linux Instance Using SSH - Amazon Elastic Compute Cloud
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- EC2 with S3 usage
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- How to Copy Data from Amazon S3 to Amazon Elastic Block Store (EBS)
- How to Create an AWS EC2 Instance with Python
- How to Fix "WARNING: UNPROTECTED PRIVATE KEY FILE!" on Mac and Linux
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- Python: Demystifying AWS' Boto3 - OzNetNerd
- Registry of Open Data on AWS
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- An Often Overlooked Data Science Skill - Towards Data Science
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- Five Command Line Tools for Data Science
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- SSH and SCP: Howto, tips & tricks – Linux Academy
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- 10 new tricks your old relational database can do | InfoWorld
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- Building a Data Science Development Environment With Docker Compose
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- Cloning a repository - User Documentation
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- Example of Portfolio IO website
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- Tips For Data Scientists To Write Good Code
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- (5) Google Colab 101 in 5 Minutes Flat - YouTube
- 3 More Google Colab Environment Management Tips
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- gcloud dataproc clusters create | Cloud SDK | Google Cloud
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- GDELT-Event_Codebook-V2.0.pdf
- GDELT-Global_Knowledge_Graph_Codebook-V2.1.pdf
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- Getting Started With Google Colab - Towards Data Science
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- Google Cloud Platform Pricing Calculator | Google Cloud Platform | Google Cloud
- Google Codelabs
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- Installing Google Cloud SDK | Cloud SDK Documentation | Google Cloud
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- IPython Magics for BigQuery — google-cloud-bigquery 0.1.0 documentation
- Python Client for Google BigQuery — google-cloud-bigquery 0.1.0 documentation
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- Quotas & limits | BigQuery | Google Cloud
- Standard SQL | BigQuery | Google Cloud
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- Command Line Tricks For Data Scientists
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- Breaking Down the Basics of an Effective Git Workflow
- git - the simple guide - no deep shit!
- Git basics - a general workflow
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- An Introduction to Latex
- Big-O Algorithm Complexity Cheat Sheet
- Big-O Algorithm Complexity Cheat Sheet (Know Thy Complexities!) @ericdrowell
- Elasticsearch Mapping: The Basics, Two Types, and a Few Examples
- Full-Stack AI: Building a UI for Your Latest AI Project in No Time at All
- Glossary of Homebrew Terms
- Homebrew Terminology
- Intro to Data Science – Acquiring Data (CSV, SQL, APIs)
- My Mac OSX Bash Profile | Nathaniel Landau
- Online LaTeX Equation Editor - create, integrate and download
- Open-sourcing Polynote: an IDE-inspired polyglot notebook
- Programming tutorials, coding problems, and practice questions | HackerEarth
- RegExr: Learn, Build, & Test RegEx
- The Unix Shell
- What are cron and crontab, and how do I use them?
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- R vs. Python: The Data Science Wars - Dataconomy
- Using Python and R together: 3 main approaches
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- Python Algorithms for Interviews - YouTube
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- What are the most important things to look for in a code review? : Python
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- Validating data format and data processing pipeline
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- A Guide to Python’s Virtual Environments - Towards Data Science
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- How can I install a previous version of Python 3 in macOS using homebrew? - Stack Overflow
- Setting up Python environment with Anaconda and Homebrew
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- Deploy a machine learning model using flask - Towards Data Science
- How to build a web application using Flask and deploy it to the cloud
- How to build an API for a machine learning model in 5 minutes using Flask
- How to Easily Deploy Machine Learning Models Using Flask
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- 34 Amazing Python Open Source Libraries (v.2019) : Python
- Cerberus Usage — Cerberus is a lightweight and extensible data validation library for Python
- d6t/d6tpipe: Push and pull data files like code
- Filter Pandas Dataframe in a Click using QGrid Library : Python
- FlashText’s documentation! — FlashText 1.0 documentation
- Knio/dominate: Dominate is a Python library for creating and manipulating HTML documents using an elegant DOM API. It allows you to write HTML pages in pure Python very concisely, which eliminate the need to learn another template language, and to take advantage of the more powerful features of Python.
- ResidentMario/missingno: Missing data visualization module for Python.
- rhiever/tpot: A Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.
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- A Beginner’s Tutorial to Jupyter Notebooks - Towards Data Science
- A new Python kernel for Jupyter – Jupyter Blog
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- Bringing the best out of Jupyter Notebooks for Data Science
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- 7. Input and Output — Python 3.6.5 documentation
- 8.1. datetime — Basic date and time types — Python 2.7.14 documentation
- 8.3. collections — High-performance container datatypes — Python 2.7.14 documentation
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- Combine Python dictionaries that have the same Key name - Stack Overflow
- Creating a dictionary with list of lists in Python - Stack Overflow
- Merge two rows in a csv file in Python - Stack Overflow
- Python - Display rows with repeated values in csv files - Stack Overflow
- python - How to combine 2 csv files with common column value, but both files have different number of lines - Stack Overflow
- python - Merge two tables (CSV) if (table1 column A == table2 column A) - Stack Overflow
- python - sort csv by column - Stack Overflow
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- Linear Algebra Essentials with Numpy (part 1) - Towards Data Science
- Linear Algebra Essentials with Numpy (part 2) - Towards Data Science
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- Python Numpy Tutorial
- Test Support (numpy.testing) — NumPy v1.17 Manual
- Working With Numpy Matrices: A Handy First Reference
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- All the basics of Python classes - Level Up Coding
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- 'yield' and Generators Explained
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- 15 Python tips and tricks, so you don’t have to look them up on Stack Overflow
- 20 Python Snippets You Should Learn Today - Better Programming - Medium
- 25 Useful Python Snippets to Help in Your Day-to-Day Work
- 30 Helpful Python Snippets That You Can Learn in 30 Seconds or Less
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- How To Do Just About Anything With Python Lists
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- Statistical Data Analysis in Python
- Survival Analysis to Explore Customer Churn in Python
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- The "Python Machine Learning (2nd edition)" book code repository and info resource
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- The Python Graph Gallery
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- Top 20 Python libraries for data science in 2018 | ActiveWizards: data science and engineering lab
- Top 30 Python Libraries for Machine Learning - Morioh
- Top 50 matplotlib Visualizations - The Master Plots (w/ Full Python Code) | ML+
- trekhleb/learn-python: 📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
- Understanding Python Decorators in 12 Easy Steps!
- Useful String Methods in Python - Towards Data Science
- Using Pip in a Conda Environment - Anaconda
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- Weekly Digest for Data Science and AI: Python and R (Volume 2)
- Weekly Digest for Data Science and AI: Python and R (Volume 3)
- Weekly Python Digest for Data Science (1st Week July)
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- 3 steps to a clean dataset with Pandas – Towards Data Science
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- Data-Science--Cheat-Sheet/Pandas at master · abhat222/Data-Science--Cheat-Sheet
- Flattening JSON objects in Python - Towards Data Science
- Getting more value from the Pandas’ value_counts() - Towards Data Science
- Group By: split-apply-combine — pandas 0.19.2 documentation
- How to use Pandas the RIGHT way to speed up your code
- Index, Select, And Filter pandas Dataframes - Python
- Learn Advanced Features for Python’s Main Data Analysis Library in 25 Minutes
- Pandas GroupBy: Your Guide to Grouping Data in Python – Real Python
- Pandas Pivot Table Explained - Practical Business Python
- Pandas Profiling To Boost Exploratory Data Analysis
- Pandas testing functions
- Reshaping and pivot tables — pandas 0.25.0 documentation
- Sorting data frames in pandas - Towards Data Science
- Styling — pandas 0.25.2 documentation
- Tutorials — pandas 0.19.2 documentation
- Visualization — pandas 0.19.2 documentation
- What's the future of the pandas library?
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- line_profiler · PyPI
- Optimizing Your Code Using Profilers - Help | PyCharm
- Profiling and optimizing your Python code | Toucan Toco
- Profiling Python Like a Boss - The Zapier Engineering Blog | Zapier
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- A Beginner’s Guide to the Python time Module – Real Python
- An Effective Python Environment: Making Yourself at Home – Real Python
- Cool New Features in Python 3.8 – Real Python
- Documenting Python Code: A Complete Guide – Real Python
- Get Started With Django Part 1: Build a Portfolio App – Real Python
- Getting Started With Python IDLE – Real Python
- Getting Started With Testing in Python – Real Python
- How to Iterate Through a Dictionary in Python – Real Python
- How to Use Generators and yield in Python – Real Python
- How to Use sorted() and sort() in Python – Real Python
- How to Write Beautiful Python Code With PEP 8 – Real Python
- Inheritance and Composition: A Python OOP Guide – Real Python
- Invalid Syntax in Python: Common Reasons for SyntaxError – Real Python
- Natural Language Processing With spaCy in Python – Real Python
- NumPy arange(): How to Use np.arange() – Real Python
- Object-Oriented Programming (OOP) in Python 3 – Real Python
- Primer on Python Decorators – Real Python
- Pure Python vs NumPy vs TensorFlow Performance Comparison – Real Python
- PyCharm for Productive Python Development (Guide) – Real Python
- Python 3's f-Strings: An Improved String Formatting Syntax (Guide) – Real Python
- Python 3's pathlib Module: Taming the File System – Real Python
- Python API Tutorials – Real Python
- Python args and kwargs: Demystified – Real Python
- Python Exceptions: An Introduction – Real Python
- Python sleep(): How to Add Time Delays to Your Code – Real Python
- Python's Instance, Class, and Static Methods Demystified – Real Python
- Reading and Writing Files in Python (Guide) – Real Python
- Thinking Recursively in Python – Real Python
- Three Ways of Storing and Accessing Lots of Images in Python – Real Python
- Understanding the Python Mock Object Library – Real Python
- Unicode & Character Encodings in Python: A Painless Guide – Real Python
- Using the Python zip() Function for Parallel Iteration – Real Python
- When to Use a List Comprehension in Python – Real Python
- Working With Files in Python – Real Python
- Working With JSON Data in Python – Real Python
- Writing Beautiful Pythonic Code With PEP 8 – Real Python
- Writing Comments in Python (Guide) – Real Python
- Your Guide to the Python Print Function – Real Python
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- A simple introduction to Test Driven Development with Python
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- 10 tips to improve your plotting - Towards Data Science
- 10 Useful Python Data Visualization Libraries for Any Discipline
- 5 Python Libraries for Creating Interactive Plots
- Bokeh Tutorial
- Data Visualization in Python: Matplotlib vs Seaborn
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- Getting Started with Plot.ly - Towards Data Science
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- 10 Tools to Help You Learn R
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- 100 Free Tutorials for Learning R
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- 7 Simple Data Visualizations You Should Know in R
- A Complete Tutorial to learn Data Science in R from Scratch
- A Complete Tutorial to learn Data Science in R from Scratch
- A Demo of Hierarchical, Moderated, Multiple Regression Analysis in R
- Anomaly Detection in R | Open Data Science
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- Cheatsheets – RStudio
- Cheatsheets – RStudio
- Comparison with R / R libraries — pandas 0.22.0 documentation
- Comprehensive Beginners Guide to Learn Data Visualization in R | Learn R
- Computing Classification Evaluation Metrics in R | R-bloggers
- Conjoint Analysis in R: A Marketing Data Science Coding Demonstration
- Control Structures in R: Using If-Else Statements and Loops
- CRAN Task View: Econometrics
- CRAN: Contributed Documentation
- Daily news about R
- Data Cleaning and Wrangling With R - Data Science Central
- Data Frame | R Tutorial
- Data Science Live Book
- Data Scientist with R Track | DataCamp
- DataCamp – Statistical Modeling in R (Part 1) | Data Sci Guide
- Demystifying ggplot2
- Do Faster Data Manipulation using These 7 R Packages
- Exploratory Data Analysis in R (introduction) | R-bloggers
- Exploratory Data Analysis… by Roger D. Peng [PDF/iPad/Kindle]
- Factors in R --- Open Data Science Conference
- Feature Selection : Select Important Variables with Boruta Package
- Filter data with dplyr – learn data science
- Forecasting Using R
- Frequencies analysis in R
- Group-By Modeling in R Made Easy | Open Data Science
- How to make any plot in ggplot2? | ggplot2 Tutorial
- How to use RStudio code snippets | InfoWorld
- Implementation of 17 classification algorithms in R
- Interactive Tutorial on Dirichlet Processes Using R Shiny | R-bloggers
- Introduction to Generalized Linear Models in R - Including Sample Code
- Introduction to ggplot2 — the grammar - Data Science Central
- Introduction to R Software : NPTEL | Paperwrk
- IRkernel
- June 2018: Top 40 New Packages | R-bloggers
- Learning Data Science on R - Step by Step Guide Learning Path
- Learning R in Seven Simple Steps - Data Science Central
- List of useful packages (libraries) for Data Analysis in R
- One-page R: a survival guide to data science with R - Data Science Central
- OnePageR – Togaware
- Online Learning – RStudio
- PacktPublishing/R-Programming-By-Example: R Programming By Example, published by Packt
- Predicting Airline Delays – Jesse Steinweg-Woods, Ph.D. – Data Scientist
- Quick Guide to R and Statistical Programming - Data Science Central
- Quick Introduction to ggplot2
- Quick-R: Home Page
- R code for book covering the fundamentals of data visualization
- R courses
- R Documentation and manuals | R Documentation
- R for Big Data in One Picture - Data Science Central
- R for Data Science
- R graphics
- R Graphics Cookbook
- R Interview Questions And Answers | R Programming Interview Questions 2016
- R Lang: Zero to Hero – Towards Data Science
- R Learning Path: From beginner to expert in R in 7 steps
- R Learning Path: From beginner to expert in R in 7 steps
- R packages for summarising data – part 2 – Dabbling with Data
- R Programming for Data… by Roger D. Peng [PDF/iPad/Kindle]
- R tutorial (R programming basic 101) - Data Science Central
- R tutorial to produce nice graphs and maps with 256 colors - AnalyticBridge
- R-bloggers | R news and tutorials contributed by (750) R bloggers
- Regression Models for Data… by Brian Caffo [PDF/iPad/Kindle]
- rep function | R Documentation
- Response Modeling using Machine Learning Techniques in R - Data Science Central
- RPubs - Data Processing with dplyr & tidyr
- rstudio/webinars: Code and slides for RStudio webinars
- Shiny - Tutorial
- Support Vector Regression in R
- Survey Analysis in SQL and R - Open Data Science - Your News Source for AI, Machine Learning & more
- swirl: Learn R, in R.
- Text Processing in R
- The Art of Data Visualization: Learn 7 visualizations in R
- The R Inferno book
- Three Strategies for Working with Big Data in R · R Views
- tidyr 0.3.0 | RStudio Blog
- Time based heatmaps in R - Data Science Central
- Top 20 R Machine Learning and Data Science packages
- Top 20 R packages by popularity
- Top R Packages for Machine Learning
- Using Linear Regression for Predictive Modeling in R
- Using themes in ggplot2 | R-bloggers
- Webinars – RStudio
- Welcome · Advanced R
- What R's most popular tools say about data science — Quartz
- Wrangling data in the Tidyverse - Part 1 - YouTube
- xray: The R Package to Have X Ray Vision on Your Datasets | Open Data Science
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- London House Prices Stats Explorer (2017-18)
- Not Hotdog: A Shiny app using the Custom Vision API | R-bloggers
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- Advanced Programming | SAS
- advanced-programmer.pdf
- Amazon.com: SAS Certification Prep Guide: Advanced Programming for SAS 9, Fourth Edition (9781629593548): SAS Institute: Books
- SAS Tutorial : Beginner to Advanced
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- SPARQL Cheat Sheet
- Your First SPARQL Query · GitBook
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- 24 Essential SQL Interview Questions and Answers | Toptal
- 46 Questions on SQL to test a data science professional (Skilltest Solution)
- 7 Steps to Mastering SQL for Data Science
- Data Science with SQL in Python - Towards Data Science
- DataCamp: Intro to SQL for Data Science
- Dataform | Three tables every analyst needs
- enochtangg/quick-SQL-cheatsheet: A quick reminder of all SQL queries and examples on how to use them.
- Getting Started with PostgreSQL on Mac OSX | Codementor
- How To Ace Data Science Interviews: SQL – Towards Data Science
- Intro to SQL for Data Scientists
- Intro to SQL for Data Scientists
- Learning SQL 201: Optimizing Queries, Regardless of Platform
- PostgreSQL Exercises
- PostgreSQL: Window Functions
- Setting up databases with PostgreSQL, PSequel, and Python
- SQL Cheat Sheet Download PDF it in PDF or PNG Format
- SQL for Beginners. Learn basics of SQL in 1 Hour - YouTube
- SQL Online Course: Introduction | Pluralsight
- SQL Summer Camp: Getting started with SQL | Kaggle - YouTube
- SQL Tutorial: How To Write Better Querie (article) - DataCamp
- SQL Window Functions Tutorial for Business Analysis
- SQLBolt - Learn SQL - Introduction to SQL
- Switching Between MySQL, PostgreSQL, and SQLite
- Techniques for improving the performance of SQL queries under workspaces in the Data Service Layer
- The Last SQL Guide for Data Analysis You’ll Ever Need
- The SQL Tutorial for Data Analysis | SQL Tutorial - Mode Analytics
- The SQL Tutorial for Data Analysis | SQL Tutorial - Mode Analytics
- The SQL Tutorial for Data Analysis | SQL Tutorial - Mode Analytics
- Top Handy SQL Features for Data Scientists
- Want a Job in Data? Learn This
-
- Stata Cheat Sheet - Data Science Central
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- barryclark/jekyll-now: Build a Jekyll blog in minutes, without touching the command line.
- Clearing Up Confusion Around baseurl – Again | By Parker
- Creating a GitHub Pages site - GitHub Help
- Five Minutes to Your Own Website - Towards Data Science
- How to create a multilevel list in HTML
- HTML5 UP! Responsive HTML5 and CSS3 Site Templates
- Jekyll • Simple, blog-aware, static sites | Transform your plain text into static websites and blogs
- Pelican Static Site Generator, Powered by Python
- poole/hyde: A brazen two-column theme for Jekyll.
- Using a custom domain with GitHub Pages - User Documentation
-
Application to BusinessBack to Top
- 150 successful machine learning models: 6 lessons learned at Booking.com – the morning paper
- What I’ve Learned Doing Data Science and Analytics at 8 Different Companies and 4 Jobs in 6 Years
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- Ad Astra Per Alas Porci
- Airbnb Engineering & Data Science – Medium
- Alex Woods blog
- Blog - healthcare.ai
- Blog - Machine Learning Plus
- Blog - Naftali Harris: Statistician, Hacker and Climber
- Blog | Greg Reda
- Blog | Open Data Science
- Blog | The Data Incubator
- Chang Hsin Lee – Committing my thoughts to words.
- ClaoudML - Randy Lao's site (DS resources)
- Data @ Quora - Quora
- Data Science – Towards Data Science
- Data Science Case Study: Classification in IoT – Towards Data Science – Medium
- Data Science Unicorn
- Dataconomy Home - Dataconomy
- DataIsBeautiful
- DataQuest blog
- DataSciGuide | The Data Science Learning Directory
- DataTau
- Econometrics By Simulation
- FOXY DATA SCIENCE - Blog
- Healthy Algorithms | A blog about algorithms, combinatorics, and optimization applications in global health informatics.
- Home | Pythonic Perambulations
- Imran Khan
- Learn OpenCV ( C++ / Python )
- Machine Learning with R: An Irresponsibly Fast Tutorial
- Mark Meloon - Helping You Get a Job As a Data Scientist
- No Free Hunch | The Official Blog of Kaggle.com
- Open Data Science - Your Data Science News Source for AI & Beyond
- Simply Statistics
- Statistical Modeling, Causal Inference, and Social Science
- Statistical Thinking
- Twitch
- William Chen Website
- Yanir Seroussi | Data science and beyond
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- 10 Free Must-Read Books for Machine Learning and Data Science
- 20 Handbooks on Modern Statistical Methods - Data Science Central
- 23 Free Data Science Books
- 5 EBooks to Read Before Getting into A Machine Learning Career
- A Comprehensive Guide to Machine Learning
- A programmer's guide to data mining
- Amazon.com: Python Crash Course: A Hands-On, Project-Based Introduction to Programming (9781593276034): Eric Matthes: Books
- Applied Data Science
- Art of Data Science par Roger D. Peng et al. [PDF/iPad/Kindle]
- Automate the Boring Stuff with Python
- Automate the Boring Stuff with Python
- Bruce Hansen's Econometrics Text
- causality - The Book of Why by Judea Pearl: Why is he bashing statistics? - Cross Validated
- Data Science from Scratch with Python: Step-by-Step Beginner Guide for Statistics, Machine Learning, Deep learning and NLP using Python, Numpy, Pandas, Scipy, Matplotlib, Sciki-Learn, TensorFlow 2, Peter Morgan - Amazon.com
- Deep Learning
- Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.
- Forecasting: Principles and Practice (eBook)
- Free Book: Statistics -- New Foundations, Toolbox, and Machine Learning Recipes - Data Science Central
- Free Data Ebook Archive - O'Reilly Media
- Free Data Science and Big Data Ebooks - O'Reilly Media
- free-programming-books | :books: Freely available programming books
- Fundamentals of Data Visualization (online reading)
- Interpretable Machine Learning
- Introduction · A Byte of Python (eBook)
- Introduction to Statistical Learning with Applications in R
- List of Free Must-Read Machine Learning Books - Data Science Central
- Machine Learning and Big Data
- Master Machine Learning Algorithms
- Mining of Massive Datasets
- New Book: Mastering Machine Learning Algorithms - Data Science Central
- Python Data Science Handbook | Python Data Science Handbook
- Read Statistical inference for data science | Leanpub
- Statistical inference for data… by Brian Caffo [PDF/iPad/Kindle]
- The Book of Why
- The Data Science Handbook
- The Pragmatic Programmer: From Journeyman to Master: 8601404321023: Computer Science Books @ Amazon.com
- Think Bayes – Green Tea Press
- Think Stats 2e – Green Tea Press
- Think Stats: Probability and Statistics for Programmers
- Why every data scientist shall read “The Book of Why” by Judea Pearl
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- Cooladata: Behavioral Data Analysis and Visualization
- ThinkData Works - Solving Data Variety
- Travel startups are taking off | TechCrunch
-
- Demystifying Data Science Recordings | Metis
- Machine Learning for Healthcare
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-
- Universal Class for Libraries
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- 15 Mathematics MOOCs for Data Science
- 30 Free Courses: Neural Networks, Machine Learning, Algorithms, AI - Data Science Central
- A/B Testing | Udacity
- Colab | fast.ai course v3
- Computer Science: Free Courses Online | Open Culture
- DataScienceSpecialization/courses: Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
- Here are 300 free Ivy League university courses you can take online right now – Quartz
- I ranked every Intro to Data Science course on the internet, based on thousands of data points
- Managing Big Data with MySQL | Coursera
- My favorite free courses to learn data structures and algorithms in depth
- Practical Deep Learning for Coders, v3 | fast.ai course v3
- The top 5 Big Data courses to help you break into the industry
- Top Data Science, Machine Learning Courses from Udemy
- Top Three Online Data Science Courses for 2020 - Data Science Central
- Twitter Sentiment Analysis | Analytics Vidhya
- www.cs.cornell.edu/courses/cs4780/2018fa/lectures/index.html
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-
- Corsica | NHL Team Stats
- NHL Stats, History, Scores, & Records | Hockey-Reference.com
- python - Need help scraping an NHL statistics table with lxml and xpath - Stack Overflow
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- 10 Great Healthcare Data Sets - Data Science Central
- 100+ Interesting Data Sets for Statistics - rs.io
- 17 places to find datasets for data science projects
- 19 Free Public Data Sets For Your First Data Science Project - Springboard Blog
- 19 Free Public Data Sets For Your First Data Science Project | Springboard Blog
- 19 Sources for eye-opening, credible consumer research data - WP Premium Support
- 25 Open Datasets for Deep Learning Every Data Scientist Must Work With
- 70 Amazing Free Data Sources You Should Know
- 70+ websites to get large data repositories for free
- 8 Scene Categories Dataset
- A Brief Introduction to Wikidata – Learn how to query data from Wikipedia
- A topic-centric list of high-quality open datasets in public domains. By everyone, for everyone!
- Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)
- Awesome Data Science Repository - Data Sets
- Awesome Public Datasets on GitHub
- Big Data: 33 Brilliant And Free Data Sources Anyone Can Use
- caesar0301/awesome-public-datasets: An awesome list of high-quality open datasets in public domains (on-going). By everyone, for everyone!
- Cline Center Historical Phoenix Event Data | Cline Center
- Dataset list — A list of the biggest machine learning datasets
- Datasets for data cleaning practice
- Datasets for Natural Language Processing
- DoDs Joint AI Center to open-source natural disaster satellite imagery data set
- Download images and metadata from a Wikimedia Commons category or results page
- fast.ai Datasets
- Free Public Datasets
- GeoLite2 Free Downloadable Databases « MaxMind Developer Site
- How to Research a Quotation | The New York Public Library
- Introducing VisualData: A Search Engine for Computer Vision Datasets
- Irma and Paul Milstein Division of United States History, Local History and Genealogy - NYPL Digital Collections
- KITTI Vision Benchmark Suite - Registry of Open Data on AWS
- Large Datasets Repository | Public Datasets on AWS
- MED Summaries dataset
- Mining Twitter Data with Python Part 1: Collecting Data
- OEDA Datasets
- Our Data | FiveThirtyEight
- Peeling back the curtain – The Economist
- Places2: A Large-Scale Database for Scene Understanding
- Quotables | Kaggle
- Search | Quandl
- SUN Attribute Dataset
- SUN Database
- The 50 Best Free Datasets for Machine Learning - Gengo AI
- The 50 Best Public Datasets for Machine Learning – Data Driven Investor – Medium
- The GDELT Project
- The KITTI Vision Benchmark Suite
- The new fast.ai research datasets collection, on AWS Open Data · fast.ai
- Top 10 Road Trip Youtube Channels To Follow
- Uber Movement: Let's find smarter ways forward
- UCI Machine Learning Repository
- UCI Machine Learning Repository
- US Census American Community Survey on AWS
- UT-Austin Computer Vision Group Datasets
- VisualData - Search Engine for Computer Vision Datasets
- WildDash Benchmark
- yoosan/video-understanding-dataset: A collection of recent video understanding datasets, under construction!
-
- Building A Data Science Product in 10 Days
- What is Minimum Viable (Data) Product?
-
- 4 Reasons Why Economists Make Great Data Scientists (And Why No One Tells Them)
- How can I get into Data Science with an economics degree? - Quora
- Machine-Learning-and-Econometrics.pdf
-
- Quantitative Economics
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- Data Scientist Job at Miles | AngelList
-
- Flickr - OpenStreetMap Wiki
- Map Features - OpenStreetMap Wiki
- Mapillary - OpenStreetMap Wiki
- OpenStreetCam - OpenStreetMap Wiki
- Overpass turbo/Wizard - OpenStreetMap Wiki
- Photo linking - OpenStreetMap Wiki
- Photo mapping - OpenStreetMap Wiki
- Planet OSM (complete copies of OSM database)
- rossant/smopy: OpenStreetMap image tiles in Python
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- 35 Years Of American Death | FiveThirtyEight
- All The Pubs In Britain & Ireland & Nothing Else – Brilliant Maps
- An Introduction to Satellite Imagery and Machine Learning | Azavea
- Analysing tube journeys with Folium
- Analyzing Geographic Data with QGIS - Part 1 - Data Science Central
- boston-airbnb-geo/boston-airbnb-geo.ipynb at master · ResidentMario/boston-airbnb-geo
- Calculate distance and bearing between two Latitude/Longitude points using haversine formula in JavaScript
- Comparing US City Street Orientations - Geoff Boeing
- Create a Heat Map from your Google Location History in 3 easy Steps
- Databases and data access APIs - OpenStreetMap Wiki
- Deep learning in Satellite imagery - Appsilon Data Science | End to End Data Science Solutions
- Developers and Local Governments are Using Location Intelligence for Optimal Real Estate Decision-making
- Download GeoLife GPS Trajectories from Official Microsoft Download Center
- GeoDa Data and Lab
- GeoGuessr - Let's explore the world!
- GeoJSON
- Get an API Key | Maps JavaScript API | Google Developers
- GPS Visualizer
- GPSPhoto · PyPI
- Hivemapper - Build Maps that see and reveal changes
- How does the Bay Area Commute? – Towards Data Science
- How to make a gif map using Python, Geopandas and Matplotlib
- How to quickly join data by location in Python — Spatial join
- How to replicate Google Maps distance using Python : Python
- K-Means Clustering Applied to GIS Data
- Links - Learn Spatial Analysis | Center for Spatial Data Science
- Loading Data from OpenStreetMap with Python and the Overpass API
- Locations you can see from on top of Mt Everest [1158 x 575] : MapPorn
- Make a Location-Based Web App With Django and GeoDjango – Real Python
- Mapping American Community Survey (ACS) Data Just Got Easier
- Microsoft Releases 125 million Building Footprints in the US as Open Data | Maps Blog
- OpenStreetMap Data to ML Training Labels for Object Detection
- OSM file formats - OpenStreetMap Wiki
- Predicting School Performance with Census Income Data
- Quickly Find Businesses Along a Route | Search Quality Insights
- Resources Archive - OSGeo
- Retrieving OpenStreetMap data — Geo-Python - AutoGIS documentation
- River Maps - Grasshopper Geography
- Spatial autocorrelation & co
- Spatial data, GeoPandas, and Pokémon: Part I – Towards Data Science
- Top 10 Map Types in Data Visualization - Towards Data Science
- Tutorials - Learn Spatial Analysis | Center for Spatial Data Science
- under the raedar: Mapping the Polycentric Metropolis: journeys to work in the Bay Area
- Visualising Geospatial data with Python using Folium
- Well-known text representation of geometry - Wikipedia
- What Is Your Favorite Python Library For Visualizing Geospatial Data? - Data Science Central
- Беллингкэт - Сбор геопространственных данных веб-скрейпингом - Беллингкэт
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- Adding Basemaps from Google or Bing in QGIS? - Geographic Information Systems Stack Exchange
- Download QGIS | MacOS Packages of QGIS
- Introduction to GIS
- mac - QGIS 3.4.0 system freeze on MacOS 10.14 - Geographic Information Systems Stack Exchange
- Nearest Neighbor Analysis — QGIS Tutorials and Tips
- PyQGIS 101: Introduction to QGIS Python programming for non-programmers | Free and Open Source GIS Ramblings
- qgis - Installing QGIS3 on Mac? - Geographic Information Systems Stack Exchange
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- 48 Companies Bringing AI to Healthcare | Redox
- A revolution: 10 use cases of artificial intelligence in healthcare
- BetterDoctor :: Meetup Recap: Provider Data Quality Must be Fixed
- DNA Sequence Data Analysis — Starting off in Bioinformatics
- Early Prediction of Sepsis from Clinical Data -- the PhysioNet Computing in Cardiology Challenge 2019 v1.0.0
- Generating Neural Networks to Detect Alzheimer's
- How Real-Time & Location Data Are Revolutionizing the Healthcare Industry
- Machine Learning 101: 5 Easy Steps for Using it in Healthcare
- Machine learning in population health: Opportunities and threats
- Making Better Use of Health Care Data
- The 7 Organizations That Will Turn Healthcare Upside Down In 2016
- The AI/ML Opportunity Landscape in Healthcare. Do It Right or It Will be More of a Mine Field. - Data Science Central
- Using Big Data and Predictive Analytics to Improve Healthcare | Search Technologies
- Using Electronic Health Records to predict future diagnosis codes with Gated Recurrent Units
-
- Advertising & Marketing Fundamentals For Data Scientists - Data Science Central
- Customer Profiling and Segmentation in Ecommerce - Data-Mania, LLC
- Don't Have a Marketing Data Scientist? You Don't Know What You're Missing
- Market Mix Modeling (MMM) — 101 – Towards Data Science
- Market Mix Modeling | SAS Programming
-
- A Data Scientist’s Guide to Open Source Licensing - Towards Data Science
- Contributing — scikit-learn 0.21.3 documentation
- How to Contribute to Open Source | Open Source Guides
-
- 10+2 Data Science Methods that Every Data Scientist Should Know in 2016 - Data Scientist TJO in Tokyo
- 16 Useful Advices for Aspiring Data Scientists | LinkedIn
- 24 Ultimate Data Science Projects To Boost Your Knowledge and Skills (& can be accessed freely)
- 25 Big Data Terms Everyone Should Know - Dataconomy
- 4 Reasons to Start Participating in Data Science Hackathons
- 42 Steps to Mastering Data Science
- 5 Data Science Projects That Will Get You Hired in 2018
- 5 Steps to Launch Your Data Science Career (with Python)
- 5 Things You Need To Know About Data Science
- 6 Techniques Which Help Me Study Machine Learning Five Days Per Week
- 7 Super Simple Steps From Idea To Successful Data Science Project
- 8 Useful Advices for Aspiring Data Scientists
- 9 Must-have skills you need to become a Data Scientist, updated
- A Day in the Life of a Data Scientist
- A Day in the Life of a Data Scientist: Part 4
- Advice to Aspiring Data Scientists - DZone Big Data
- AnalyticBridge - Data Intelligence, Business Analytics
- Building a Data Science Portfolio: A Newcomer's Guide - Data-Mania
- Building Data Dictionaries – Haystacks
- Data extraction tools for beginners and professionals
- Data Helpers
- Data Science | Trello
- Data Science Central
- Data Science Cheat Sheet - Data Science Central
- Data science concepts you need to know! Part 1 – Towards Data Science
- Data Science for Startups: Business Intelligence – Towards Data Science
- Data Science is Boring (Part 2)
- Data Science Project Ideas | The Data Incubator
- Data Science Simplified Articles
- Data science test | TestDome.com
- Data Science vs Decision Science - Towards Data Science
- Data Scientia | Data Science | AI | Machine Learning | IoT
- Data Scientist Resume Projects – Stats and Bots
- DataResponsibly - Course | Data Responsibly Courses
- DataSciGuide | The Data Science Learning Directory
- GA Data Science Example Student Projects
- GA Gallery
- GitHub - bulutyazilim/awesome-datascience: An awesome Data Science repository to learn and apply for real world problems.
- How Do You Win the Data Science Wars? You Cheat By Doing The Necessary Pre-work! - Data Science Central
- How Quantitative UX Research Differs from Data Analytics
- How should you structure your Data Science and Engineering teams? · fast.ai
- How to Become More Marketable as a Data Scientist
- How To Do User Segmentation Right – A Practical Guide for Data Analysts | Open Data Science
- How To Go Into Data Science: Ultimate Q&A for Aspiring Data Scientists with Serious Guides
- Life Is Study
- Made at Metis | Metis
- Not Just a Title: How to Identify a Data Scientist - Burtch Works
- Podcasts, Twitter, and Newsletters: Rounding out your data science education | Springboard
- Preparing for the Transition to Data Science
- Progression Of A Data Scientist - Sequoia Capital Publication - Medium
- Sample Projects for Data Scientists in Training - Data Science Central
- Six categories of Data Scientists - Data Science Central
- Skills, Work Experience, And Education Of 1,001 Data Scientists In 2019
- Some Data Science Certifications Worth Considering - Data Science Central
- Standing Out in a Sea of Data Scientists - Towards Data Science
- The 3 Missing Roles that every Data Science Team needs to Hire
- The Data Science Industry: Who Does What (Infographic) (article) - DataCamp
- The Doing Part of Learning Data Science
- The Future of Analytics and Data Science
- The Hackathon Guide for Aspiring Data Scientists
- The most comprehensive Data Science learning plan for 2017
- The Must-Have Skills You Need to Become a Data Scientist - Burtch Works
- The Must-Have Skills You Need to Become a Data Scientist - Burtch Works
- THE PSYCHOLOGY OF DATA SCIENCE – THE GROUP OF ANALYSTS
- The question about Data Science that everyone’s asking
- The secret sauce for growing from a data analyst to a data scientist
- The Self-Taught Data Scientist Curriculum - Data Mania
- Top 10 Data Science Resources on Github
- Top 10 Data Science Skills, and How to Learn Them - Dataconomy
- Top Data Science Resources on the Internet Right Now - Data Science Central
- Understanding the Changing Position Roles in Data Science - Data Science Central
- Want a job in data science? You might have to take a standardized test when applying - Chicago Tribune
- What 70% of Data Science Learners Do Wrong
- What Great Data Analysts Do — and Why Every Organization Needs Them
- What Is Data Science?
- What Is Data Science?
- When our Data Science Team Didn’t Produce Value - Towards Data Science
- Which Data Science Skills are core and which are hot/emerging ones?
- Why you’re not a job-ready data scientist (yet) - Towards Data Science
- William Chen's answer to How can I become a data scientist? - Quora
-
- 150+ Business Data Science Application in Python - Towards Data Science
- Top 12 Data Science Use Cases in Government - Data Science Central
- Top 6 Data Science Use Cases in Design - Data Science Central
- Top 9 Ways Artificial Intelligence Prevents Fraud
- We are finally getting better at predicting organized conflict - MIT Technology Review
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- kennethreitz.org
- Numan Yilmaz – Welcome to the World of Data Science
- Rajat Gupta
- Ryan T. Lee
- Steven's Blog
- www.randigriffin.com
- Yu Cheng
-
- Best Data Science Podcasts (2017)
- Chris Albon Podcast Episodes
- Podcast Archive - SuperDataScience - Big Data | Analytics Careers | Mentors | Success
- Podcast recommendations
- The Ultimate List of Data Science Podcasts – Real Python
- Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning
- Trends in data science with O’Reilly Media’s Chief Data Scientist
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- Advice on Building Data Portfolio Projects - Jason Goodman - Medium
- Crafting Superb Data Science Resume and Portfolio - Towards Data Science
- Data Science Portfolios That Will Get You the Job – Dataquest
- How to Build a Data Science Portfolio - Towards Data Science
- How to Create an Amazing Data Science Portfolio - Towards Data Science
- How to Showcase the Impact of Your Data Science Work
- My 5 Favorite Data Science Portfolios - Towards Data Science
-
- 5 Phases To Successfully Complete a Data Science Project - Data Science Central
- A Guide to Basic Data Analysis | Geckoboard
- Data Science Project Flow for Startups – Towards Data Science
- Home - Cookiecutter Data Science
- How to plan and execute your ML and DL projects
- 10 Rules for Creating Reproducible Results in Data Science - Dataconomy
- Fantastic Four of Data Science Project Preparation
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- Data Science for Startups: Introduction - Towards Data Science
-
- 6 Steps to Storytelling Your Data Like a Senior Data Scientist — Coding with Max
- Data Storytelling: Deliver Insights via Compelling Stories | Udemy
- The Art of Story Telling in Data Science and how to create data stories?
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-
- Tableau in 10 Minutes: Step-by-Step Guide - Data Science Central
- The Ultimate Cheat Sheet on Tableau Charts – Towards Data Science
- Gallery | Tableau Public
- Good enough to great | Tableau Software
- Learn Tableau Tutorials Interview Questions And Resumes
- Resources | Tableau Public
- Tableau Public Visualization Makeover: US Tuition Trends
- Tableau Pie Charts, Scatter Plot, Area Fill Charts & Circular View
- Authors | Tableau Public
- How to Create a Control Chart in Tableau - Data Science Central
-
- [OC] Western Allies air missions through World War II, with period-accurate borders. : dataisbeautiful
- 11 Innovation Data Visualizations in Python, R and Tableau
- 9 Data Visualization Tools That You Cannot Miss in 2019
- A Quick Overview of Data Visualization - DZone Big Data
- All buildings in the Netherlands, shaded by year of construction
- Data visualization - Material Design
- Data Viz Project | Collection of data visualizations to get inspired and finding the right type.
- Data-Science--Cheat-Sheet/Data Visualization at master · abhat222/Data-Science--Cheat-Sheet
- DataViz: D3
- How to Tell a Powerful Story with Data Visualization
- Interactive Data Visualization with Modern JavaScript and D3 — SitePoint
- Kevin Quealy website (graphics editor at NYT)
- Modern Visualization for the Data Era - Plotly
- Renters and Owners — Visualizing every person in the US.
- storytelling with data
- The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization
- Top 16 Types of Chart in Data Visualization - Towards Data Science
- Viz of the Day - powered by FeedBurner
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- 5 Things to Know Before Rushing to Start in Data Science
- 6 Proven Steps to Land a Job in Data Science - Data Science Central
- Advice on building a machine learning career and reading research papers by Prof. Andrew Ng
- Aspiring Data Scientists - Get Hired! - Data Science Central
- Career Outcomes Matter - Career Coaching by Melissa Llarena
- Certificates and Certification in Analytics, Data Mining, and Data Science
- Data Science Career Paths: Different Roles in the Industry - Springboard Blog
- Hiring Unicorns – Clover Health
- How Do I Get My First Data Science Job?
- How to Become a Data Scientist: The Definitive Guide
- How to Get a Start with a Career in Data Science | Open Data Science
- Learn Data Science - 2018 Guide To The Best Data Science Bootcamps
- Preparing Your Data Science Resume & Portfolio – Towards Data Science
- Setting Yourself Up for Success in Data Science - Webinar Notes | LinkedIn
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- 21 Must-Know Data Science Interview Questions and Answers
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- 40 Interview Questions asked at Startups in Machine Learning / Data Science
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- 50 Most Common Interview Questions - Glassdoor Blog
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- 51 Interview Questions To Ask In An Interview | The Muse
- 66 job interview questions for data scientists - Data Science Central
- 66 job interview questions for data scientists - Data Science Central
- 7 Tips for a Successful Interview – Optimize Guide
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- A Modern Approach To Successful Job Interviews
- Acing the AI Interview — Part 1 – Acing AI – Medium
- Acing the AI Interview — Part 2 – Acing AI – Medium
- Course Report: How to Ace The Data Science Interview? | Metis Blog
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- Data Interview Questions | Ace your next data science interview
- Data Science & ML : A Complete Interview Guide | Dimensionless
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- Data-Science--Cheat-Sheet/Interview Questions at master · abhat222/Data-Science--Cheat-Sheet
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- Employers of Reddit, what mistakes do people make during interviews without knowing? : AskReddit
- Every Data Science Interview Boiled Down To Five Basic Questions
- Every Data Science Interview Boiled Down To Five Basic Questions
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- How to Answer "What's Your Biggest Weakness?" (Video) | Interviewing Tips | The Muse
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- I've held 1000 interviews, and there are only 4 questions that matter - Business Insider
- I've held 1000 interviews, and there are only 4 questions that matter - Business Insider
- I’m A Hiring Manager—Here Are Five Questions I Always Ask Job Candidates
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- Job interview tricks that will pay off forever - Business Insider
- Job interview tricks that will pay off forever - Business Insider
- Job: Interview Flashcards - Cram.com
- Making Data Science Interviews Better - Towards Data Science
- Mentr - Tech Interview Prep
- Mock Interview - LeetCode
- Netflix Data Science Interview Questions — Acing the AI Interview
- Paypal Data Science Interview Questions - Acing AI - Medium
- Phone Screening Interview Questions | Robert Half
- Phone Screening Interview Questions | Robert Half
- Questions From Data Science Interviews | Udacity
- Questions to ask in a job interview - Business Insider
- RPubs - 111 Data Science Interview Questions with Detailed Answers
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- The 30 Most Important Interview Questions to Ask This Summer - Glassdoor Blog
- The 30 Most Important Interview Questions to Ask This Summer - Glassdoor Blog
- The 45 Questions You Should Ask In Every Job Interview - Glassdoor Blog
- The Best Interview Questions We've Ever Published | First Round Review
- The Data Science Interview - Your data interview training platform.
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- Top 10 Job Interview Questions and Answers — Job Interview Tools
- Top Data Science Interview Questions For Budding Data Scientists | Edureka Blog
- What I Learned From Interviewing With Top Data Science Teams — Tips for Aspiring Data Scientists
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- Infographic: The Typical Data Scientist Profile in 2019 - Data Science Central
- Job Search Mastery in 9 Steps – Lightwork
- Naval Ravikant's Guide To Choosing Your First Job In Tech | AngelList
- reaching out to a hiring manager with questions before applying for a job — Ask a Manager
- Revealing questions to ask on a first date - Business Insider
- Search Jobs, Career Advice and Company Profiles at The Muse
- SF Immersives - Job Search Resources - Google Docs
- SF Immersives - Job Search Resources - Google Docs
- Some Reflections on Being Turned Down for a Lot of Data Science Jobs | tdhopper.com
- Stop missing out on hidden jobs (and internships) | Rohan Punamia | Pulse | LinkedIn
- Ten Job Search Hacks Everybody Needs To Know
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- The Successful Data Science Job Hunt – Towards Data Science
- The Ultimate Job Search Guide | The Muse
- Top 10 List for Data Science Job Seekers | LinkedIn
- What Getting A Job In Data Science Might Look Like – Towards Data Science
- What to Avoid: Common Mistakes on Data Science Applications
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- Action Verbs | Harvard Law School
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- Data Scientists - How To Perfect Your Resume! - Data Science Central
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- My Personal Formula for a Winning Resume | Laszlo Bock | Pulse | LinkedIn
- My Personal Formula for a Winning Resume | LinkedIn
- Optimize Your Resume and Boost Interview Chances - Jobscan
- Resume makeover: We helped a highly-experienced recruiter
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- What do Hiring Managers Look For in a Data Scientist’s CV? | LinkedIn
- Write a Better Resume: FlexJobs' Resume Expert Answers Your Questions - FlexJobs
- Writing a Resume for a Data Science Career – Towards Data Science
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- Getting started with Elasticsearch in Python – Towards Data Science
- Hadoop Tutorial for Beginners: Hadoop Basics - BMC Software
- Hadoop vs. Spark: A Head-to-Head Comparison - DZone Big Data
- MLlib: Main Guide - Spark 2.3.0 Documentation
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- Apache Spark - A Complete Spark Tutorial for Beginners - DataFlair
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- Apache Spark in Python: Beginner's Guide (article) - DataCamp
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- apache-spark eBook
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- Big Data Analysis Using PySpark | Codementor
- Book - Learning Apache Spark with Python
- Cheat sheet PySpark Python.indd
- Cluster Mode Overview - Spark 2.4.4 Documentation
- Complete Guide on DataFrame Operations in PySpark
- Comprehensive Introduction - Apache Spark, RDDs & Dataframes (PySpark)
- Creating a PySpark project with pytest, pyenv, and egg files
- Data Science for Startups: PySpark - Towards Data Science
- First Steps With PySpark and Big Data Processing – Real Python
- Google Cloud Platform for data scientists: using Jupyter Notebooks with Apache Spark on Google Cloud | Google Cloud Blog
- Google Cloud Platform for data scientists: using Jupyter Notebooks with Apache Spark on Google Cloud | Google Cloud Blog
- How to use PySpark on your computer – Towards Data Science
- Introduction to Apache Spark
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- MLlib: Main Guide - Spark 2.4.4 Documentation
- PacktPublishing/PySpark-Cookbook: PySpark Cookbook, published by Packt
- Pandas to PySpark Conversion Cheatsheet - Justin's Blog
- Practical Apache Spark in 10 minutes. Part 2 - RDD - Data Science Central
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- PySpark Cheat Sheet: Spark in Python (article) - DataCamp
- PySpark in Google Colab - Towards Data Science
- PySpark Tutorial | Learn Apache Spark Using Python | Edureka
- PySpark Tutorial-Learn to use Apache Spark with Python
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- Running PySpark in a Jupyter Notebook on Google Cloud | Imran Khan
- Spark | Udacity
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- training-data-analyst/PySpark-Test-Solution.ipynb at master · GoogleCloudPlatform/training-data-analyst
- Use Cloud Dataproc, BigQuery, and Apache Spark ML for Machine Learning | Cloud Dataproc Documentation | Google Cloud
- Useful Things to Know when Starting with PySpark and Databricks - Justin's Blog
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- Welcome to Spark Python API Docs! — PySpark master documentation
- What is Apache Spark - MapR
- Introduction to Spark with Python
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- The Ultimate guide to AI, Data Science & Machine Learning, Articles, Cheatsheets and Tutorials ALL in one place | LinkedIn
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- Logistic Regression Example in Python (Source Code Included)
- Logistic Regression in One Picture - Data Science Central
- Logistic Regression Vs Decision Trees Vs SVM: Part I - Edvancer Eduventures
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- Embeddings | Kaggle
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- Grokking-Deep-Learning: this repository accompanies my forthcoming book "Grokking Deep Learning"
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- Home - deeplearning.ai
- Homepage | DeepLearningItalia
- How Autoencoders Work: Intro and UseCases | Kaggle
- How Deep Neural Networks Work - YouTube
- How Do Artificial Neural Networks Learn? – Towards Data Science
- How to build a deep learning model in 15 minutes – tech-at-instacart
- How to Grid Search Hyperparameters for Deep Learning Models in Python With Keras
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- How to use early stopping properly for training deep neural network? - Cross Validated
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- lexfridman/mit-deep-learning: Tutorials, assignments, and competitions for MIT Deep Learning related courses.
- Machine Learning is Fun! Part 3: Deep Learning and Convolutional Neural Networks
- Manning | Grokking Deep Learning
- Mario vs. Wario: Image Classification in Python – Towards Data Science
- Mastering the Learning Rate to Speed Up Deep Learning
- Matrix Multiplication in Neural Networks - Data Science Central
- MIT 6.S191: Convolutional Neural Networks - YouTube
- MIT Deep Learning
- MIT Introduction to Deep Learning - TensorFlow - Medium
- mit-deep-learning/deep_learning_basics.ipynb at master · lexfridman/mit-deep-learning
- Module 20 - Building Neural Network Application Using TensorFlow | engMRK
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- Optimization Algorithms in Deep Learning - Towards Data Science
- Optimizing Neural Networks — Where to Start? – Towards Data Science
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- Practical Guide of RNN in Tensorflow and Keras - Paul’s Blog
- Preventing Deep Neural Network from Overfitting – Towards Data Science
- Rajat2712/Deep-Learning-Studio
- ResNet, AlexNet, VGGNet, Inception: Understanding various architectures of Convolutional Networks – CV-Tricks.com
- Rules-of-thumb for building a Neural Network - Towards Data Science
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- Tensors Explained - Data Structures of Deep Learning - deeplizard
- The 5 Computer Vision Techniques That Will Change How You See The World
- The 9 Deep Learning Papers You Need To Know About (Understanding CNNs Part 3) – Adit Deshpande – CS Undergrad at UCLA ('19)
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- The Mathematics of Data Science: Understanding the foundations of Deep Learning through Linear Regression - Data Science Central
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- Uncertainty Quantification in Deep Learning - inovex-Blog
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- Understanding Learning Rates and How It Improves Performance in Deep Learning
- Understanding Neural Networks. From neuron to RNN, CNN, and Deep Learning - Data Science Central
- Understanding the 3 Primary Types of Gradient Descent
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- What are the advantages of ReLU over sigmoid function in deep neural networks? - Cross Validated
- What is a Neural Network? - Towards Data Science
- What is the Role of the Activation Function in a Neural Network?
- When Does Deep Learning Work Better Than SVMs or Random Forests?
- Why is my validation loss lower than my training loss? - PyImageSearch
- Why Relu? Tips for using Relu. Comparison between Relu, Leaky Relu, and Relu-6.
- WTF is a Tensor?!?
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- Chainer: A flexible framework for neural networks
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- Application of RNN for customer review sentiment analysis
- Introduction to Recurrent Neural Networks | Rubik's Code
- LSTM for time series prediction - Towards Data Science
- Recurrent Neural Networks by Example in Python – Towards Data Science
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- 5 Important Changes Coming with TensorFlow 2.0 - Level Up Coding
- An Introduction to Implementing Neural Networks using TensorFlow
- Announcement: TensorFlow 2.0 is coming! – Towards Data Science
- Building Convolutional Neural Networks with Tensorflow – Ahmet Taspinar
- Building Recurrent Neural Networks in Tensorflow – Ahmet Taspinar
- Building Robust Production-Ready Deep Learning Vision Models in Minutes
- Checking in on TensorFlow 2.0: Keras, API cleanup, and more - O'Reilly Media
- Coding TensorFlow - YouTube
- Colab: An easy way to learn and use TensorFlow – TensorFlow – Medium
- Combining multiple TensorFlow Hub modules into one ensemble network with AdaNet
- Convolutional Neural Net in Tensorflow – Good Audience
- Data Augmentation Techniques in CNN using Tensorflow
- Effective TensorFlow 2.0: Best Practices and What’s Changed
- Exercise: TensorFlow Programming | Kaggle
- Get started with Google Colaboratory (Coding TensorFlow) - YouTube
- Getting Started with TensorFlow: A Machine Learning Tutorial
- Google AI Blog: Introducing AdaNet: Fast and Flexible AutoML with Learning Guarantees
- Guide - Low Level Intro
- How Not To Program the TensorFlow Graph
- How to (quickly) Build a Tensorflow Training Pipeline
- Hvass-Labs/TensorFlow-Tutorials: TensorFlow Tutorials with YouTube Videos
- Image Classification using Deep Neural Networks — A beginner friendly approach using TensorFlow
- Installing Tensorflow in Anaconda on macOS – Distributed Consciousness
- Kyubyong/tensorflow-exercises: TensorFlow Exercises - focusing on the comparison with NumPy.
- MIT Deep Learning Basics: Introduction and Overview with TensorFlow
- Python Deep Learning tutorial: Create a GRU (RNN) in TensorFlow - Data Science Central
- Stop Installing Tensorflow using pip for performance sake!
- TensorFlow 1.x vs 2.x. – summary of changes - Data Science Central
- TensorFlow 2.0 + Keras Crash Course.ipynb - Colaboratory
- TensorFlow 2.0 + Keras Crash Course.ipynb - Colaboratory
- TensorFlow 2.0 is now available! - TensorFlow - Medium
- TensorFlow in Anaconda - Anaconda
- TensorFlow Style Guide | TensorFlow
- TensorFlow Tip of the Week - YouTube
- TensorFlow World 2019 - All Sessions - YouTube
- TensorFlow: Building Feed-Forward Neural Networks Step-by-Step
- TensorFlowOnSpark brings TensorFlow programs onto Apache Spark clusters
- The APIs for Neural Networks in TensorFlow | The Data Incubator
- Transfer Learning with TensorFlow - Colaboratory
- tutorials/PytorchTensorflowMnist.ipynb at master · onnx/tutorials
- Understanding Dataflow graphs in TensorFlow - Data Science Central
- What are Symbolic and Imperative APIs in TensorFlow 2.0?
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- 20+ FFmpeg Commands For Beginners - OSTechNix
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- [Coursera] Neural Networks for Machine Learning — Geoffrey Hinton 2016 - YouTube
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- Breakthrough/PySceneDetect: A Python/OpenCV-based scene detection program, using threshold/content analysis on a given video.
- Continuous video classification with TensorFlow, Inception and Recurrent Nets
- CRCV | Center for Research in Computer Vision at the University of Central Florida
- Deep learning Tutorial for Video Classification using Python
- Face Detection in Python Using a Webcam – Real Python
- Faster video file FPS with cv2.VideoCapture and OpenCV - PyImageSearch
- Five video classification methods implemented in Keras and TensorFlow
- How to Download YouTube Videos - PCMag.com
- Image and Video Processing in Python – Python For Engineers
- Intelligent Search: Video summarization using machine learning | Search Quality Insights
- kezhang-cs/Video-Summarization-with-LSTM: Implementation of our ECCV 2016 Paper (Video Summarization with Long Short-term Memory)
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- mit-deep-learning/tutorial_driving_scene_segmentation.ipynb at master · lexfridman/mit-deep-learning
- opencv - Python - Extracting and Saving Video Frames - Stack Overflow
- python - How to set time interval to get frames from input video? - Stack Overflow
- SlowFast – Dual-mode CNN for Video Understanding | Lyrn.AI
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Dimensionality reductionBack to Top
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- Dimensionality Reduction with Principal Component Analysis, and a Mallet
- Feature Extraction Techniques - Towards Data Science
- Feature Selection and Dimensionality Reduction Using Covariance Matrix Plot
- In Depth: Principal Component Analysis | Python Data Science Handbook
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- PCA_Image_Reconstruction_and_such.ipynb
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- Seven Techniques for Data Dimensionality Reduction
- Seven Techniques for Data Dimensionality Reduction | KNIME
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction — umap 0.3 documentation
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- Bias Variance Decompositions using XGBoost - Open Data Science
- Boosting in Machine Learning and the Implementation of XGBoost in Python
- Boosting with AdaBoost and Gradient Boosting – The Making Of… a Data Scientist – Medium
- Comparing Decision Tree Algorithms: Random Forest vs. XGBoost
- Complete Guide to Parameter Tuning in Gradient Boosting (GBM) in Python
- Complete Guide to Parameter Tuning in XGBoost (with codes in Python)
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- Ensemble Learning: 5 Main Approaches
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- Ensemble Methods in One Picture - Data Science Central
- Ensemble methods: bagging, boosting and stacking - Towards Data Science
- Feature importance in random forests when features are correlated – Mathemathinking
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- Selecting good features – Part III: random forests | Diving into data
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- The Boosting Approach to Machine Learning | LinkedIn
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- CS229: Machine Learning - Projects
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- Feature Engineering vs Feature Selection | Feature Labs
- Feature Engineering: Data scientist's Secret Sauce ! | Ashish Kumar | Pulse | LinkedIn
- Feature Engineering: Data scientist's Secret Sauce ! | LinkedIn
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- Feature Selection For Unsupervised Learning - Data Science Central
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- Introductio to Variable and Feature Selection
- Kaggle: how to deal with features having high cardinality
- Methods for Selection of Important Features in Machine Learning | LinkedIn
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- Quick Feature Engineering with Dates Using fast.ai
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- What machine learning algorithms are good for estimating which features are more important? - Cross Validated
- Why, How and When to Scale your Features – GreyAtom – Medium
- Feature Engineering and Selection: A Practical Approach for Predictive Models
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- Ideas on interpreting machine learning - O'Reilly Media
- Interpreting machine learning models – Towards Data Science
- Machine Learning Explainability | Kaggle
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- Markov_Chains/Markov Notes.ipynb at master · Smeths/Markov_Chains
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- An Overview of Topics Extraction in Python with Latent Dirichlet Allocation
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- brexit-analysis/Brexit analysis with MonkeyLearn.ipynb at master · monkeylearn/brexit-analysis
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- Data-Science--Cheat-Sheet/NLP at master · abhat222/Data-Science--Cheat-Sheet
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- Harvard Text Analysis course notes
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- Named Entity Recognition with NLTK and SpaCy – Towards Data Science
- Named Entity Recognition: A Practitioner’s Guide to NLP
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- Natural Language Processing (NLP) Techniques for Extracting Information | Search Technologies
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- The complete guide for topics extraction in Python – Towards Data Science
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- Your Guide to Natural Language Processing (NLP) - Data Science Central
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- Use Scikit-Learn Pipelines to clean data and train models faster
- Using AutoML to Generate Machine Learning Pipelines with TPOT
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- Predictive models in production - William High - Medium
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- harkous/geo-recommender: Building a scalable, geo-based recommender system with k-d trees, visualized using the MEAN stack
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- 9 Must-Have Datasets for Investigating Recommender Systems
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- Comprehensive Guide to build Recommendation Engine from scratch
- Evaluation Metrics for Recommender Systems – Towards Data Science
- Fast.ai Season 1 Episode 5.1 — “MOVIE RECOMMENDATION USING FASTAI “
- Machine Learning for Recommender systems — Part 1 (algorithms, evaluation and cold start)
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- Top 7 Algorithms to Know for Building Recommender Systems
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- A Complete Tutorial on Ridge and Lasso Regression in Python
- A short intro to linear regression analysis using survey data
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- How you can use linear regression models to predict quadratic, root, and polynomial functions
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- Learn how to select the best performing linear regression for univariate models
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- Regression Analysis: How Do I Interpret R-squared and Assess the Goodness-of-Fit?
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- Agile in Data Science: What is Waterfall and Agile? – Chang Hsin Lee – Committing my thoughts to words.
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- Complete guide to create a Time Series Forecast (with Codes in Python)
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- Econometric Approach to Time Series Analysis — Seasonal ARIMA in Python
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- Experience Time Series Analysis and Forecasting Methods - DZone Big Data
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- Statistical forecasting: notes on regression and time series analysis
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- Time Series Analysis with Deep Learning : Simplified
- Time Series for Dummies – The 3 Step Process
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- How Xpath Plays Vital Role In Web Scraping Part 2 - Data Science Central
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- The ultimate list of Web Scraping tools and software
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- Web Scraping News Articles in Python - Open Data Science - Your News Source for AI, Machine Learning & more
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- Web Scraping with Python: Illustration with CIA World Factbook
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- Ask Your Employees These Questions. They Will Thank You
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- AB testing ideas
- Against A/B Tests
- Causal Inference: An Indispensable Set of Techniques for Data Scientists
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- Impact evaluation (Experimental Design) - Wikipedia
- Notes and Python scripts for A/B or Split Testing
- Preference Testing: What to Do Before You Run A/B Tests | UserTesting Blog
- Top 5 mistakes with statistics in A/B testing - Towards Data Science
- What kind of A/B testing questions should I expect in a data scientist interview and how should I prepare for such questions? - Quora
- When to Run Bandit Tests Instead of A/B/n Tests
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- An Introduction to Bayesian Inference in PyStan – Towards Data Science
- Bayes Theorem in One Picture - Data Science Central
- Bayes’ Theorem: The Holy Grail of Data Science – Towards Data Science
- Bayesian Linear Regression in Python: Using Machine Learning to Predict Student Grades Part 1
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- Matching methods for causal inference: A review and a look forward
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- From Econometrics to Machine Learning - Towards Data Science
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- Master Your Hypothesis Test - Towards Data Science
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- Your Guide to Master Hypothesis Testing in Statistics
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- How to Diagnose the Missing Data Mechanism - The Analysis Factor
- Missing Data Conundrum: Exploration and Imputation Techniques
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- Multiple Imputation for Missing Data - Statistics Solutions
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- Common statistical tests are linear models (or: how to teach stats)
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- Designing an Experiment, Power Analysis
- Determining Sample Size in One Picture - Data Science Central
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- DSC - Statistical Concepts Explained in Simple English
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