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Get a hands-on introduction to machine learning with genetic algorithms using Python. Step-by-step tutorials build your skills from Hello;
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models using Python libraries such as DEAP, scikit-learn, and NumPy Key Features Explore the ins and outs of genetic algorithms with this fast;
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Search * Neural networks and genetic algorithms * Written for data engineers and scientists with experience using Python;
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problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential;
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Get a hands-on introduction to machine learning with genetic algorithms using Python. Step-by-step tutorials build your skills from Hello;
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Genetic Algorithms in Java Basics is a brief introduction to solving problems using genetic algorithms, with working projects and solutions;
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From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don't need an;
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Algorithms (GAs). The authors explain and demonstrate the validity of these cellular genetic algorithms throughout the book with equal and parallel;
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with didactical Python implementations of the algorithms, which not only allow readers to consolidate their understanding, but also provide a;
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are comfortable with the level and with our Python coding style. This book focuses on giving solutions for complex problems in data structures;
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Authoritative coverage of a revolutionary technique for overcoming problems in electromagnetic design Genetic algorithms are stochastic;
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provide you with a thorough discussion on the analysis and design of fundamental Python data structures. * Get a better understanding of advanced;
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Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python About;
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This book deals with the fundamentals of genetic algorithms and their applications in a variety of different areas of engineering and;
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robustness of genetic algorithms with the power of parallel computers, this book provides an effective and practical approach to solving path;
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analysis and design of fundamental data structures. * Includes many helpful Python code examples, with source code provided on the website. * Uses;
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Python One-Liners will show readers how to perform useful tasks with one line of Python code. Following a brief Python refresher, the book;
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Machine Learning with Spark and Python Essential Techniques for Predictive Analytics, Second Edition simplifies ML for practical uses by;
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Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs;
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. In this book, you will: Use heuristics and design fitness functions. Build genetic algorithms. Make nature-inspired swarms with ants;
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Foundations of Genetic Algorithms 1991 (FOGA 1) discusses the theoretical foundations of genetic algorithms (GA) and classifier systems;
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coverage of every image processing task with popular Python libraries Includes topics such as pseudo-coloring, noise smoothing, computing image;
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, presenting a comprehensive and fully up-to-date treatment of genetic algorithms in industrial engineering and operations research. Beginning with a;
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information Key Features Turn your designs into working software by learning the Python syntax Write robust code with a solid understanding of Python;
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Genetic and Evolutionary Methods is a compendium of articles and papers that were presented at GEM '14, an international conference that;
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