What this book covers

Chapter 1, First Steps, introduces Jupyter Notebook and demonstrates how you can have access to the data run in the tutorials.

Chapter 2, Data Munging, presents all the key data manipulation and transformation techniques, highlighting best practices for munging activities.

Chapter 3, The Data Pipeline, discusses all the operations that can potentially improve data science project results, rendering the reader capable of advanced data operations.

Chapter 4, Machine Learning, presents the most important learning algorithms available through the scikit-learn library. The reader will be shown practical applications and what is important to check and what parameters to tune for getting the best from each learning technique. ...

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