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Learn Python by Building Data Science Applications

You're reading from  Learn Python by Building Data Science Applications

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781789535365
Pages 482 pages
Edition 1st Edition
Languages
Authors (2):
Philipp Kats Philipp Kats
Profile icon Philipp Kats
David Katz David Katz
Profile icon David Katz
View More author details

Table of Contents (26) Chapters

Preface Section 1: Getting Started with Python
Preparing the Workspace First Steps in Coding - Variables and Data Types Functions Data Structures Loops and Other Compound Statements First Script – Geocoding with Web APIs Scraping Data from the Web with Beautiful Soup 4 Simulation with Classes and Inheritance Shell, Git, Conda, and More – at Your Command Section 2: Hands-On with Data
Python for Data Applications Data Cleaning and Manipulation Data Exploration and Visualization Training a Machine Learning Model Improving Your Model – Pipelines and Experiments Section 3: Moving to Production
Packaging and Testing with Poetry and PyTest Data Pipelines with Luigi Let's Build a Dashboard Serving Models with a RESTful API Serverless API Using Chalice Best Practices and Python Performance Assessments Other Books You May Enjoy

Technical requirements

Python can be very humble and does not require an advanced computer. In fact, you can run Python on a $10 Raspberry Pi or an Arduino board! The code and data we use in this book do not require any special computational power, any laptop, or any computer made after 2008. At least 2 GB of RAM, 20 GB of disk space, and an internet connection should suffice. Your operating system (OS) shouldn't be a problem either, as Python and all the tools we will use are cross-platform and work on Windows, macOS, and Linux.

Throughout the book, we'll use two main tools to write the code: Jupyter and VS Code. Both of them are free and aren't demanding.

All the code for the book is publicly available and free to access at https://github.com/PacktPublishing/Learn-Python-by-Building-Data-Science-Applications.

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