Machine Learning



Machine Learning Handbook:
Using R and Python

Dr. Karen Mazidi



Table of Contents

* Part 1 Introduction to Machine Learning and R

  * 1 - The Craft of Machine Learning (pdf) (video)
  * 2 - Learning Base R (pdf) (video) (video part 2)
  * 3 - Data Visualization in Base R (pdf) (video)
  * 4 - The Craft 1: Planning to Learn

* Part 2 Linear Models

  * 5 - Linear Regression
  * 6 - Logistic Regression
  * 7 - Naive Bayes
  * 8 - The Craft 2: Predictive Modeling 

* Part 3 Modern R

  * 9 - The Tidyverse
  * 10 - ggplot2
  * 11 - The Craft 3: Data Wrangling in R

* Part 4 Searching for Similarity

  * 12 - Instance-based Learning with kNN
  * 13 - Clustering
  * 14 - Decision Trees and Random Forests
  * 15 - The Craft 4: Feature Engineering

* Part 5 Kernel Methods and Ensemble Methods

  * 16 - Support Vector Machines
  * 17 - Ensemble Methods and XGBoost
  * 18 - The Craft 5: Learning Theory

* Part 6 Python for Machine Learning

  * 19 - Python Basics
  * 20 - Python Libraries for Machine Learning
  * 21 - Python Machine Learning Examples
  * 22 - The Craft 6: Data Wrangling with Python

* Part 7 Neural Networks

  * 23 - Neural Networks
  * 24 - Deep Learning
  * 25 - The Craft 7: Never Stop Learning

* Part 8 Modeling the World

  * 26 - Bayes Nets
  * 27 - Markov Models
  * 28 - Reinforcement Learning
  * 29 - Never Stop Learning



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