README.md

Chapter 9: Getting Started with Machine Learning in Python

This chapter introduces you to machine learning and building models using the sklearn library.

Content

We will be working in the following notebooks:

• planets_ml.ipynb: shows how to build clustering and linear regression models using the planet data
• preprocessing.ipynb: walks through various preprocessing techniques
• red_wine.ipynb: discusses how to build a classification model to predict red wine quality
• wine.ipynb: walks through creating a classification model to predict wine type

Note that the planets_data_collection.ipynb notebook contains the code used to collect the planet data.

All the datasets necessary for the aforementioned notebooks, along with information on them, can be found in the data/ directory. The end-of-chapter exercises will also use this data to practice building ML models with scikit-learn; solutions to these exercises can be found in the repository's solutions/ch_09/ directory.