00.00 Introduction

Chapter 01 - Basics

• 01.00 Jupyter Lab and Notebooks
• 01.01 Running Code in the Notebook
• 01.02 Jupyter Exercises 1
• 01.03 PyData Primer
• 01.04 Python Exercises
• 01.05 Magic
• 01.06 Jupyter Exercises 2

Chapter 02 - NumPy

• 02.00 NumPy Basics
• 02.01 NumPy Operations
• 02.02 Randomness
• 02.03 Array Algebra
• 02.04 NumPy Exercises
• 02.05 Random Walk

Chapter 03 - Matplotlib

• 03.00 Plotting Basics
• 03.01 Reference
• 03.02 Plots in Three Dimensions
• 03.03 Statistics and Plots
• 03.04 Matplotlib Exercises
• 03.05 Plotting Engines

Chapter 04 - Pandas

• 04.00 Pandas Introduction
• 04.01 Data Frames
• 04.02 Database Operations
• 04.03 Pandas Indexes as Dimensions
• 04.04 Pandas Exercises
• 04.05 Time Series
• 04.06 Metro Traffic

Chapter 05 - Data Analysis

• 05.00 Stats
• 05.01 Distributions
• 05.02 Correlation and Statistics
• 05.03 Stats Exercises
• 05.04 Why Python?
• 05.05 Die Hard

Chapter 06 - Machine Learning

• 06.00 ML Introduction
• 06.01 Monte Carlo
• 06.02 SciKit Learn Introduction
• 06.03 Is it Right?
• 06.04 Labels
• 06.05 SciKit Learn Exercises

Chapter 07 - Regularization and Features

• 07.00 Fallacies
• 07.01 Regression
• 07.02 Full Road Trip
• 07.03 Regularization
• 07.04 Text Features
• 07.05 High Dimensions
• 07.06 Evaluation Exercises

Chapter 08 - Unsupervised Learning

• 08.00 Machine Learning Groupings, Again
• 08.01 Principal Component Analysis
• 08.02 Noise Reduction
• 08.03 Non-Linearity
• 08.04 t-SNE
• 08.05 k-Means
• 08.06 Evaluate Clusters
• 08.07 Hierarchical
• 08.08 Unsupervised Learning Exercises

Chapter 09 - Supervised Learning

• 09.00 Classification vs Regression
• 09.01 Trees
• 09.02 Ensembles
• 09.03 Margins
• 09.04 People
• 09.05 Complete Procedure
• 09.06 Data Scaling
• 09.07 Model Persistence
• 09.08 Exercises

Chapter 10 - Online Learning

• 10.00 Real World Problems
• 10.01 Perceptron
• 10.02 Online Learning
• 10.03 Forest Cover
• 10.04 Artificial Neural Networks
• 10.05 ANN Concepts
• 10.06 ANN Usage
• 10.07 Image Features
• 10.08 Autoencoders
• 10.09 ANN Architectures

Appendix B - Least Squares