In this Houston Data Science meetup we will cover how to apply machine learning algorithms with the Python library Scikit-Learn.

Follow the tutorial in the Intro to Python repository in order to install the Anaconda distribution with Python 3.

• What is machine learning?
• Types of machine learning
• A typical machine learning workflow
• Overview of Scikit-Learn
• Scikit-Learn Gotchas
• Ames Housing dataset from Kaggle competition
• Remedying missing values
• Categorical vs Continuous features
• The importance of a dummy baseline model
• Building more complex models
• Cross-validation
• Parameter tuning and grid search

All work for this tutorial will take place within a Jupyter Notebook