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Python-Machine-Learning

Try to learn Python Machine Learning book by Sebastian Raschka everyday, step by step.

Chapter 1: Giving Computers the Ability to Learn from Data
Chapter 2: Training Machine Learning Algorithms for Classification
Chapter 3: A Tour of Machine Learning Classifiers Using Scikit-learn
Chapter 4: Building Good Training Sets – Data Preprocessing
Chapter 5: Compressing Data via Dimensionality Reduction
Chapter 6: Learning Best Practices for Model Evaluation and Hyperparameter Tuning
Chapter 7: Combining Different Models for Ensemble Learning
Chapter 8: Applying Machine Learning to Sentiment Analysis
Chapter 9: Embedding a Machine Learning Model into a Web Application
Chapter 10: Predicting Continuous Target Variables with Regression Analysis
Chapter 11: Working with Unlabeled Data – Clustering Analysis
Chapter 12: Training Artificial Neural Networks for Image Recognition
Chapter 13: Parallelizing Neural Network Training with Theano

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