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Learn Python by Building Data Science Applications

Learn Python by Building Data Science Applications

By : Kats, Katz
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Learn Python by Building Data Science Applications

Learn Python by Building Data Science Applications

3 (3)
By: Kats, Katz

Overview of this book

Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.
Table of Contents (26 chapters)
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Section 1: Getting Started with Python
11
Section 2: Hands-On with Data
17
Section 3: Moving to Production

Preparing the Workspace

Welcome! We're very excited to start learning and building things with you! However, we need to get ourselves ready first.

In this chapter, we'll learn how to download and install everything you'll need throughout the book, including Python itself, all the Python packages that we'll need, and two development tools we will be using extensively: Jupyter and Visual Studio Code (VS Code). After that, we'll go through a brief overview of Jupyter and VS Code interfaces. Finally, you will run your very first line of Python, so we need to ensure that everything is ready before we dive in.

In this chapter, we'll cover the following:

  • The minimum computer configuration required
  • How to install the Anaconda distribution
  • How to download the code for this book
  • Setting up and getting familiar with VS Code and Jupyter
  • Running your first line...
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Learn Python by Building Data Science Applications
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