Step 1: Basic Python Skills
install Anaconda
including numpy, scikit-learn, and matplotlib
Step 2: Foundational Machine Learning Skills
Unofficial Andrew Ng course notes
Tom Mitchell Machine Learning Lectures
Step 3: Scientific Python Packages Overview
numpy - mainly useful for its N-dimensional array objects
pandas - Python data analysis library, including structures such as dataframes
matplotlib - 2D plotting library producing publication quality figures
scikit-learn - the machine learning algorithms used for data analysis and data mining tasks
Step 4: Getting Started with Machine Learning in Python
iPython Notebook Overview
An Introduction to scikit-learn
Example Machine Learning Notebook
Model Evaluation
Step 5: Machine Learning Topics with Python
k-means Clustering
Decision Trees
Linear Regression
Logistic Regression
Step 6: Advanced Machine Learning Topics with Python
Support Vector Machines
Kaggle Titanic Competition (with Random Forests)
Dimensionality Reduction
Step 7: Deep Learning in Python
Neural Networks and Deep Learning
Theano
Caffe