marcharper / ds_ml_resources

Data Science and Machine Learning resources, a curated list

Data Science and Machine Learning Resources

Model / Algorithm Visualizations and Playgrounds

• Best Visualizations of 2016
• Many Nice Demos
• Trees and Gradient Boosting
  • Nice Visualization of Gradient Boosting
  • Gradient Boosing Explained Visually
• Neural Networks
  • Neural Network Visualization with TensorFlow
  • Neural Networks, Manifolds, and Topology
• Clustering
  • Awesome Demo of k-Means by N. Harris
  • Awesome Demo of DBSCAN by N. Harris

Datasets

• OpenML
• A curated list of public data sets
• r/datasets
• Data.gov: US Govt released data sets
• Where Can I Find Large Public Data Sets?
• Large AWS Datasets: Data sets available through Amazon Web Services
• Github Packaged Datasets
• Data sets: Part 1 Part 2
• Financial Data
• Datasets.co

General Community

• DataTau a reddit / Hacker News style data science link-sharing site. Great for finding links and articles!
• r/datascience
• Meetup.com: Depending on your location there may be many Data Science Meetups nearby!
• DataScience Stack Exchange

Blogs and People

• Unofficial Google Data Science Blog
• Netflix Tech Blog
• A Big list of DS Blogs
• A Nice list of Data Science Blogs
• Great Article on Data Science and people to follow
• DataGenetics: Nice Visualizations and Write-ups on a variety of topics

Practitioners:

• Wes McKinney's blog
• Randal Olson's blog
• Colah's blog: Lots of interesting content on neural networks
• Austin Rochford's blog
• Andrew Gelman: Nice blog on statistics
• Curated List of Influential Data Scientists

Jobs, Salary, Interviews

Salary and Negotiation

• 2016 Data Science Salary Survey
• [https://blog.step.com/2016/04/08/an-open-source-project-for-tech-salaries/](Google, Facebook, Amazon, and Microsoft Salaries)
• What Factors Increase Your Data Science Salary
• 10 Rules for Negotiating

Interviewing

• 100 Common Interview Questions
• An Analysis of Many Data Science Interviews

Transitioning to Data Science

• Building a Data Science Portfolio
• Becoming a Data Scientist
• Leaving Academia
• Data Science Resumes: Advice on constructing a resume for data science positions
• More Resume Tips
• Interview Tips
• How to Become a Data Scientist
• Open Source Data Science Masters

Sharpening Your Reasoning Skills

• Habits of highly mathematical people
• 52 Concepts To Add To Your Cognitive Toolkit

Learning Data Science

Data Science Basics in Python

• Data Science Python: Many useful links
• Python Data Science Primer: Jupyter notebooks for pandas, matplotlib, scikit-learn, and more
• Learn Pandas by doing -- Exercises for pandas
• From Python to Numpy

Nice Jupyter Notebooks

• Some Jupyter Notebook Tricks
• Gallery of Jupyter/IPython notebooks
• Another Gallery of Jupyter/IPython Notebookss
• Building a Data Science Portfolio
• Probability
• XGBoost Walkthrough
• Notebook on Signal Processing

NLP: Natural Language Programming

• Notebook on Text Processing and Modeling by Peter Norvig
• Another Nice NLP Notebook
• On Word Embeddings

Big Data

• Practice Spark, Hadoop, etc.

Bayesian Methods

• Bayesian Data Analysis Overview
• Bayesian Data Analysis Book pdf
• Bayesian Methods and pymc

Neural Networks

• Neural Networks Demystified: Video series on NN basics
• Universal Approximation Theorem Demo
• A Curated List of Recurrent Neural Network Resources
• Tensor Flow Examples
• Tensor Flow Resources
• Variational Autoencoders
• Neural Network Zoo

Deep Learning

• Learn Deep Learning the Hard Way
• Deep Learning Projects Ranked by github stars
• 2016 Deep Learning Year In Review

Reinforcement Learning

• Simple Reinforcement Learning with Tensorflow -- multiarticle series
• Demystifying Deep Reinforcement Learning -- multiarticle series
• Deep Reinforcement Learning: Pong from Pixels
• Deep-Q learning Pong with Tensorflow and PyGame

Logistic Regression

• Logistic Regression Part 1 Part 2

Bandits and A/B testing

• Netflix A/B testing
• Multi-arm Bandits

Awesome Tools

• TPOT is a Python tool that automatically creates and optimizes machine learning pipelines using genetic programming.

Git

• Git Workflow Basics
• Learn Git
• Git Tips

Textbooks (Free)

• Machine Learning Book with Jupyter Notebooks
• Data Science Textbook: free PDF
• Probabilistic Programming & Bayesian Methods for Hackers
• Biomedical Data Science Book: Includes much preliminary material

Courses

• Machine Learning for Software Engineers
• General Assembly's Part Time DS Course
• ML course by Nando de Freitas at Oxford

Algorithms

• Top 10 Machine Learning Algorithms
• Top 10 Algorithms for Data Mining
• A Tour of Machine Learning Algorithms
• Bayesian Methods

Articles

• Approaching (Almost) Any Machine Learning Problem
• Analyzing Fonts with RNN
• Questions Each State Googles More Than Any Other State
• The Neflix Stack -- A high level overview of technologies and tools at Netflix
• Deep Learning Trends at ICLR 2016
• Automatically Categorizing Yelp Businesses
• 3 Ideas to Add to Your Data Science Toolkit
• Long Term Forecasting with Machine Learning Models

Companies

• Visual Representation of the Big Data Landscape

Understanding the Machine

• CPU Costs of Many Operations

Data Visualization and Inforgraphics

• Choosing the Right Estimator with scikit-learn
• Visualizations of U.S. public data
• Who Marries Whom?: Visualizations of job pairings in US couples

Games

• Guess the Correlation

Los Angeles

• DataScience.LA: Meetups
• Hack for LA
• Los Angeles (City) Open Data
• Los Aneleges (County) Open Data
• OpenDataLA

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