readme files

Author: rasbt

code/ch01/README.md

@@ -1,9 +1,17 @@
 Sebastian Raschka, 2015
 
-# Python Machine Learning - Chapter 1 Code
+# Python Machine Learning 
+
+# Chapter 1 Code Examples
+
+## Giving Computers the Ability to Learn from Data
+
+<hr>
 
 **Chapter 1 does not contain any code examples.**
 
+<hr>
+
 ## Installing Python packages
 
 Python is available for all three major operating systems — Microsoft Windows, Mac OS X, and Linux — and the installer, as well as the documentation, can be downloaded from the official Python website: https://www.python.org.

code/ch02/README.md

@@ -1,3 +1,6 @@
 Sebastian Raschka, 2015
 
-# Python Machine Learning - Chapter 2 Code Examples
+# Python Machine Learning 
+# Chapter 2 Code Examples
+
+## Training Machine Learning Algorithms for Classification

code/ch03/README.md

@@ -1,3 +1,6 @@
 Sebastian Raschka, 2015
 
-# Python Machine Learning - Chapter 3 Code Examples
+# Python Machine Learning 
+# Chapter 3 Code Examples
+
+## A Tour of Machine Learning Classifiers Using Scikit-learn

code/ch04/README.md

@@ -1,3 +1,6 @@
 Sebastian Raschka, 2015
 
-# Python Machine Learning - Chapter 4 Code Examples
+# Python Machine Learning 
+# Chapter 4 Code Examples
+
+## Building Good Training Sets – Data Preprocessing

code/ch05/README.md

@@ -1,9 +1,6 @@
 Sebastian Raschka, 2015
 
-# Python Machine Learning - Chapter 2 Code
+# Python Machine Learning 
+# Chapter 5 Code Examples
 
-The content is organized as follows:
-
-- `code/`: the main IPython notebook with the code example as they appear in the chapter.
-- `data/`: optional offline version(s) of the dataset(s)
-- `figures/`: notebook figures and color figures
+## Compressing Data via Dimensionality Reduction

code/ch06/README.md

@@ -0,0 +1,9 @@
+Sebastian Raschka, 2015
+
+# Python Machine Learning 
+
+# Chapter 6 Code Examples
+
+##  Learning Best Practices for Model Evaluation and Hyperparameter Tuning
+
+

code/ch07/README.md

@@ -0,0 +1,6 @@
+Sebastian Raschka, 2015
+
+# Python Machine Learning 
+# Chapter 7 Code Examples
+
+## Combining Different Models for Ensemble Learning

code/ch08/README.md

@@ -0,0 +1,6 @@
+Sebastian Raschka, 2015
+
+# Python Machine Learning 
+# Chapter 8 Code Examples
+
+## Applying Machine Learning to Sentiment Analysis

code/ch09/README.md

@@ -0,0 +1,6 @@
+Sebastian Raschka, 2015
+
+# Python Machine Learning
+# Chapter 9 Code Examples
+
+## Embedding a Machine Learning Model into a Web Application

code/ch10/README.md

@@ -0,0 +1,6 @@
+Sebastian Raschka, 2015
+
+# Python Machine Learning 
+# Chapter 10 Code Examples
+
+## Predicting Continuous Target Variables with Regression Analysis

code/ch11/README.md

@@ -0,0 +1,6 @@
+Sebastian Raschka, 2015
+
+# Python Machine Learning 
+# Chapter 11 Code Examples
+
+## Working with Unlabeled Data – Clustering Analysis

code/ch12/README.md

@@ -0,0 +1,6 @@
+Sebastian Raschka, 2015
+
+# Python Machine Learning 
+# Chapter 12 Code Examples
+
+## Training Artificial Neural Networks for Image

code/ch13/README.md

@@ -0,0 +1,6 @@
+Sebastian Raschka, 2015
+
+# Python Machine Learning 
+# Chapter 13 Code Examples
+
+## Parallelizing Neural Network Training with Theano

code/datasets/README.md

@@ -9,5 +9,5 @@ Sebastian Raschka, 2015
 
 ### wine.data
 
-- used in chapters 4
+- used in chapters 4, 5
 - source: [https://archive.ics.uci.edu/ml/datasets/Wine](https://archive.ics.uci.edu/ml/datasets/Wine)