Artificial Intelligence Programming with Python: From Zero to Hero - Tapa blanda

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PERRY XIAO, PhD, is Professor and Course Director of London South Bank University. He holds his doctorate in photophysics and is Director and co-Founder of Biox Systems Ltd., a university spin-out company that designs and manufactures the AquaFlux and Epsilon Permittivity Imaging system.

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Your start-to-finish roadmap to AI programming with Python

Artificial intelligence remains one of the most exciting areas of computer science in modern history. It has applications in everything from people management to finance, and opens a world of possibilities for programmers, computer scientists, and other technology professionals.

In Artificial Intelligence Programming with Python^®: From Zero to Hero, distinguished photophysicist and veteran educator Dr. Perry Xiao shows you how to harness the power of the Python programming language to accelerate your introduction to AI coding.

The book demystifies the concepts of artificial intelligence and teaches you its fundamentals from scratch, using plain, simple language and illustrative code examples.

Divided into three easy-to-understand sections, the book explains general concepts in AI, machine learning, and deep learning. The author also tackles a variety of practical subjects, like classification, regression in machine learning, and generative adversarial networks.

Artificial Intelligence Programming with Python^® presents hands-on introductions to Python and other widely used software tools, as well as expansive discussions of supervised, semi-supervised, and unsupervised machine learning. You’ll also get quick reference “cheat sheet” guides for artificial intelligence programming in Python that you can use again and again.

A can’t-miss guide for anyone with a basic knowledge of programming—including familiarity with variables, arrays, loops, if-else statements, and file input and output—this book also offers:

• Thorough introductions to AI, machine learning, and deep learning
• Descriptions of Python
• Discussions of supervised and unsupervised learning
• Explorations of classification and regression in supervised learning
• Explanations of clustering, PCA, and LDA in unsupervised learning
• Fulsome treatments of deep learning, cloud computing, and edge computing