Books & Videos

Table of Contents

  1. Chapter 1 Using R

    1. R for Machine Learning

    2. Further Reading on R

  2. Chapter 2 Data Exploration

    1. Exploration vs. Confirmation

    2. What is Data?

    3. Inferring the Types of Columns in Your Data

    4. Inferring Meaning

    5. Numeric Summaries

    6. Means, Medians, and Modes

    7. Quantiles

    8. Standard Deviations and Variances

    9. Exploratory Data Visualization

    10. Visualizing the Relationships between Columns

  3. Chapter 3 Classification: Spam Filtering

    1. This or That: Binary Classification

    2. Moving Gently into Conditional Probability

    3. Writing Our First Bayesian Spam Classifier

  4. Chapter 4 Ranking: Priority Inbox

    1. How Do You Sort Something When You Don’t Know the Order?

    2. Ordering Email Messages by Priority

    3. Writing a Priority Inbox

  1. Works Cited