1. Fundamentals
Overview
This chapter introduces you to supervised learning, using Anaconda to manage coding environments, and using Jupyter notebooks to create, manage, and run code. It also covers some of the most common Python packages used in supervised learning: pandas, NumPy, Matplotlib, and seaborn. By the end of this chapter, you will be able to install and load Python libraries into your development environment for use in analysis and machine learning problems. You will also be able to load an external data source using pandas, and use a variety of methods to search, filter, and compute descriptive statistics of the data. This chapter will enable you to gauge the potential impact of various issues such as missing data, class imbalance, ...
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