Summary

This chapter went through the core tools for data science and statistical computing in Python, namely, NumPy for linear algebra and computation, pandas for tabular data processing, and Matplotlib and Seaborn for visualization. These tools will be used extensively in later chapters of this book, and they will prove useful in your future projects. In the next chapter, we will go into the specifics of a number of statistical concepts that we will be using throughout this book and learn how to implement them in Python.

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