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Python for Programmers: with Big Data and Artificial Intelligence Case Studies

Pdf Book Name: Python for Programmers: with Big Data and Artificial Intelligence Case Studies
Author: Paul Deitel, Harvey Deitel
Publisher: Pearson Education
ISBN-10, 13: 0135224330,9780135224335
Year: 2019
Pages: 640 / 810 Pages
Language: English
File size: 27 MB
File format: PDF,EPUB

Python for Programmers: with Big Data and Artificial Intelligence Case Studies Pdf Book Description:

Welcome to Python one of the world’s most widely used computer programming languages and, according to the Popularity of Programming Languages (PYPL) Index, the world’s most popular. Here, we introduce terminology and concepts that lay the groundwork for the Python programming you’ll learn in chapters and the big­data, artificial­ intelligence and cloud based case studies we present in We’ll review object­ oriented programming terminology and concepts. You’ll learn why Python has become so popular. We’ll introduce the Python Standard Library and various data ­science libraries that help you avoid “reinventing the wheel.” You’ll use these libraries to create software objects that you’ll interact with to perform significant tasks with modest numbers of instructions. Next, you’ll work through three test­ drives showing how to execute Python code In the first, you’ll use IPython to execute Python instructions interactively and immediately see their results.

In the second, you’ll execute a substantial Python application that will display an animated bar chart summarizing rolls of a six ­sided die as they occur. You’ll see the “ Law of Large Numbers” in action. In Chapter 6, you’ll build this application with the Matplotlib visualization library. In the last, we’ll introduce Jupyter Notebooks using Jupyter Lab an interactive, web browser­ based tool in which you can conveniently write and execute Python instructions. Jupyter Notebooks enable you to include text, images, audios, videos, animations and code. In the past, most computer applications ran on standalone computers (that is, not networked together). Today’s applications can be written with the aim of communicating among the world’s billions of computers via the Internet. We’ll introduce the Cloud and the Internet of Things (IoT), laying the groundwork for the contemporary applications you’ll develop in Chapters 11. You’ll learn just how big “big data” is and how quickly it’s getting even bigger. Next, we’ll present a big­data case study on the Waze mobile navigation app, which uses many current technologies to provide dynamic driving directions that get you to your destination as quickly and as safely as possible. As we walk through those technologies, we’ll mention where you’ll use many of them in this book. The chapter closes with our first Intro to Data Science section in which we discuss a key intersection between computer science and data science—artificial intelligence. As demands for new and more powerful software are soaring, building software quickly, correctly and economically is important. Objects, or more precisely, the classes objects come from, are essentially reusable software components. There are date objects, time objects, audio objects, video objects, automobile objects, people objects, etc. Almost any noun can be reasonably represented as a software object in terms of attributes (e.g., name, color and size) and behaviors (e.g., calculating, moving and communicating). Software ­development groups can use a modular, object ­oriented design­ and ­implementation approach to be much more productive than with earlier popular techniques like “structured programming.” Object oriented programs are often easier to understand, correct and modify.

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