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Learn Python by Building Data Science Applications

Learn Python by Building Data Science Applications

By : Kats, Katz
2.8 (4)
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Learn Python by Building Data Science Applications

Learn Python by Building Data Science Applications

2.8 (4)
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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1
Section 1: Getting Started with Python
11
Section 2: Hands-On with Data
17
Section 3: Moving to Production

Preface

There are no separate systems. The world is a continuum. Where to draw a boundary around a system depends on the purpose of the discussion.
Donella H. Meadows, Thinking in Systems: A Primer

Python has become one of the most popular programming languages in the world, according to multiple polls and metrics. This popularity is, to no small extent, a direct result of the simplicity of the language, its power, and scalability, allowing it to run even large-scale applications, such as Dropbox, YouTube, and many others. It becomes even more valuable with the rise in the adoption of machine learning techniques and algorithms, including state-of-the-art algorithms on the edge of scientific advancements.

Consequently, there are hundreds of books, courses, and online tutorials on different aspects of programming, machine learning, data processing, and more. Many sources highlight the importance of learning-by-doing and building your own projects. Connecting the dots and structuring all this vast knowledge into one big picture is not an easy task. Seeing the big picture, in our opinion, is critical for the completion of any project. Indeed, there are plenty of options and decisions to take at every step. It is the grand schema of a project as a whole that helps you make those decisions, focus on what matters, and spend your time wisely.

This book is designed to be an entry point for any newcomer or novice developer, aiming to cover the whole life cycle of a data-driven application. By the end of it, you will be able to write arbitrary Python code, collect and process data, explore it, and build your own packages, dashboards, and APIs. Multiple notes and tips point to alternative solutions or decisions, allowing you to alternate code for your specific needs.

This book will be a useful resource if any of the following apply to you:

  • You have just started to code.
  • You know the basics but struggle to build something handy.
  • You know your specific domain well—whether it be statistics, machine learning, or development—but lack experience in other parts of building a project.
  • You're an experienced developer with little exposure to Python, trying to learn about the Python package's ecosystem.

If you feel you fall into any of those categories, or want to build a project from scratch for other reasons, please join us on this journey.

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