Data hacking notebooks

iPython notebooks for data hacking

Several notebooks that collate tools/notes for data hacking in one place:

• CS229 (Machine Learning), an excellent Stanford course taught by Andrew Ng.
• An Introduction to Statistical Learning by G. James, D. Witten, T. Hastie and R. Tibshirani.
• scikit-learn.
• Seaborn.
• Pandas.
• Apache Spark.

Still in development. Links to the notebooks here:

• Pandas and Seaborn for exploring data
• SQL, Postgres, and SQLAlchemy
• Basic statistics review
• Basic probability review
• Introductory machine learning notes
• Linear Regression
• Logistic Regression
• Linear Discriminant Analysis
• Naive Bayes
• Support Vector Machines
• Tree-based methods
• Cross-validation
• Dimension Reduction
• Unsupervised Learning
• Scikit-learn pipelines
• Deep Learning