Python Algorithms: Mastering Basic Algorithms in the Python Language Machine Learning, 1st Edition A Bayesian and Optimization Perspective
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Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques - together with the Bayesian inference approach, whose essence lies in the use of a hierarchy of probabilistic models
The Car Hacker's Handbook: A Guide for the Penetration Tester Machine Learning in Python: Essential Techniques for Predictive Analysis
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Modern cars are more computerized than ever. Infotainment and navigation systems, Wi-Fi, automatic software updates, and other innovations aim to make driving more ≠convenient. But vehicle technologies havenít kept pace with todayís more hostile security environment, leaving ≠millions vulnerable to attack. Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python.
Introduction to Game Development Using Processing Heterogeneous Computing with OpenCL 2.0, 1st Edition
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This book will guide you through the basic game development process, covering game development topics including graphics, sound, artificial intelligence, animation, game engines, Web-based games, etc Heterogeneous Computing with OpenCL 2.0 teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs).