Books & Videos

Table of Contents

  1. Chapter 1 Using R

    1. R for Machine Learning

  2. Chapter 2 Data Exploration

    1. Exploration versus 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

  5. Chapter 5 Regression: Predicting Page Views

    1. Introducing Regression

    2. Predicting Web Traffic

    3. Defining Correlation

  6. Chapter 6 Regularization: Text Regression

    1. Nonlinear Relationships Between Columns: Beyond Straight Lines

    2. Methods for Preventing Overfitting

    3. Text Regression

  7. Chapter 7 Optimization: Breaking Codes

    1. Introduction to Optimization

    2. Ridge Regression

    3. Code Breaking as Optimization

  8. Chapter 8 PCA: Building a Market Index

    1. Unsupervised Learning

  9. Chapter 9 MDS: Visually Exploring US Senator Similarity

    1. Clustering Based on Similarity

    2. How Do US Senators Cluster?

  10. Chapter 10 kNN: Recommendation Systems

    1. The k-Nearest Neighbors Algorithm

    2. R Package Installation Data

  11. Chapter 11 Analyzing Social Graphs

    1. Social Network Analysis

    2. Hacking Twitter Social Graph Data

    3. Analyzing Twitter Networks

  12. Chapter 12 Model Comparison

    1. SVMs: The Support Vector Machine

    2. Comparing Algorithms

  1. Works Citedbooks and publicationsbibliography ofresourcesbooks and publications; website resourcesstatisticsresources formachine learningresources forR programming languageresources for

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