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Showing 5 outstanding Python books published on

Infrastructure as Code, Patterns and Practices: With examples in Python and Terraform

by Rosemary Wang

Infrastructure as Code, Patterns and Practices you will learn how to: Optimize infrastructure for modularity and isolate dependencies Test infrastructure configuration Mitigate, troubleshoot, and isolate failed infrastructure changes Collaborate across teams on infrastructure development Update infrastructure with minimal downtime using blue-green deployments Scale infrastructure systems supporting multiple business units Use patterns for provisioning tools, configuration management, and image building Deliver secure infrastructure configuration to production
Published on : Aug. 30, 2022
Python version: TH
400 pages

The Recursive Book of Recursion: Ace the Coding Interview with Python and JavaScript

by Al Sweigart

The Recursive Book of Recursion uses Python and JavaScript examples to teach the basics of recursion, exposing the ways that it’s often poorly taught and clarifying the fundamental principles of all recursive algorithms. You’ll learn when to use recursive functions (and, most importantly, when not to use them), how to implement the classic recursive algorithms often brought up in job interviews, and how recursive techniques can help solve countless problems involving tree traversal, combinatorics, and other tricky topics.
Published on : Aug. 16, 2022
Python version: TH
328 pages
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Django 4 By Example: Build powerful and reliable Python web applications from scratch

by Antonio Mele

Django 4 By Example is the 4th edition of the best-selling franchise that helps you build web apps. This book will walk you through the creation of real-world applications, solving common problems, and implementing best practices using a step-by-step approach.
Published on : Aug. 29, 2022
Python version: TH
764 pages

Python for Data Science: A Hands-On Introduction

by Yuli Vasiliev

You will discover Python’s rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science, including NumPy, pandas, scikit-learn, matplotlib, and more. Examples show how to load data in various formats, how to streamline, group, and aggregate data sets, and how to create charts, maps, and other visualizations. Later chapters go in-depth with demonstrations of real-world data applications, including using location data to power a taxi service, market basket analysis to identify items commonly purchased together, and machine learning to predict stock prices.
Published on : Aug. 2, 2022
Python version: TH
240 pages

Effective Data Science Infrastructure: How to make data scientists productive

by Ville Tuulos

In Effective Data Science Infrastructure you will learn how to: Design data science infrastructure that boosts productivity Handle compute and orchestration in the cloud Deploy machine learning to production Monitor and manage performance and results Combine cloud-based tools into a cohesive data science environment Develop reproducible data science projects using Metaflow, Conda, and Docker Architect complex applications for multiple teams and large datasets Customize and grow data science infrastructure
Published on : Aug. 16, 2022
Python version: TH
352 pages