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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

Conda

Last, but not least, let's talk about Conda. Yes, this is a tool, developed by Anaconda, hence the name. If you installed Python via Anaconda, you have it already. Conda represents two things at the same time – a package manager, and a virtual environment manager. Let's now discuss these two roles in more detail.

First, and foremost, Conda allows you to install Python packages (and other tools). Compared to Python's original pip package manager, it is language-agnostic, and can install any type of software; this feature is vital to the data science stack, as many tools are based on code, written in the C, C#, and Fortran languages—Conda just pulls a binary suitable for your operating system, if there is one.

In order to see all the packages already installed, type conda list in your terminal, and hit Enter – this will print out all the...

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