Promising title, doesnt appear to have a table of contents currently.
Preface
Machine Learning for Hackers: Email
How This Book is Organized
Conventions Used in This Book
Using Code Examples
How to Contact Us
Using R
R for Machine Learning
Further Reading on R
Data Exploration
Exploration vs. Confirmation
What is Data?
Inferring the Types of Columns in Your Data
Inferring Meaning
Numeric Summaries
Means, Medians, and Modes
Quantiles
Standard Deviations and Variances
Exploratory Data Visualization
Visualizing the Relationships between Columns
Classification: Spam Filtering
This or That: Binary Classification
Moving Gently into Conditional Probability
Writing Our First Bayesian Spam Classifier
Ranking: Priority Inbox
How Do You Sort Something When You Don’t Know the Order?
Ordering Email Messages by Priority
Writing a Priority Inbox
Works Cited
Books
Articles
About the Authorsunfortunately I see here, that there seems to be a large part of the book spent on a statistics introduction (including R) and only one machine learning algorithm actually gets introduced. and on top of all it's one of the most simple ones (naive bayes). I expected at least some further description of support vector machines or other advanced techniques.