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Intro to Python for Computer Science and Data Science Learning to Program with AI, Big Data and the Cloud cover

Intro to Python for Computer Science and Data Science Learning to Program with AI, Big Data and the Cloud

by Paul J. Deitel, Harvey M. Deitel

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About this book

Faster and smaller hardware, larger and cheaper Internet bandwidth, and abundant and near-free software: these are some of the powerful trends in computing technologies that have emerged over the past few decades, paving the way for enormous volumes of data being generated at rapidly increasing speeds and quantities. Since the latest Innovations in programming today are "all about data"- be it data science, data analytics, big data, or databases - the autors have sealessly integrated data science into computer science topics to create a book that reaches several audiences in the field, their choice of programming language being Python. Python is an excellent forst programming language to learn for beginners, but, because of its expressive power, readability, conciseness, and interactivity, it is equally appropriate for professional programmers. Key Feature: - All the code in the book uses the Ipython interpreter, which provides a friendly, immediate-feedback, interactive mode for quickly exploring, discovering, and experimenting with Python and its extensive libraries. - The book uses Jupyter Notebooks to help meet the reproducibility recommendations of data science undergraduate curricula. Jupyter Notebooks, part of a free, open-source project, enable authors to combine text, graphics, audio, video, and interactive coding functionality for entering, editing, executing, debugging, and modifying code quickly and conveniently in a web browser. Data science topics like machine learning, deep learning, and cognitive computing covered in the later chapters see AI, big data, and cloud computing woven into them through case studies that present opportunities to use real-world datasets. - Privacy, security, and ethical challenges arising from AI and big data are discussed throughout the book from a Pyton-specific point of view, with practical and relevant examples. Over 1500 examples, exercises, and projects drawn from computer science, data science, and other fields provide an engaging introduction to Python programming. Students can attack exciting challenges with AI, big data, and cloud technologies like IBM Watson, Hadoop, Spark, or MapReduce.

Details

Format
Paperback
Pages
880
Publisher
Pearson Education Limited
Language
EN
Edition
1
ISBN-13
9781292364902
ISBN-10
1292364904

Categories

Business & Economics, Business Mathematics, Computers, Database Administration & Management