Explore the ever-growing world of genetic algorithms to build and enhance AI applications involving search, optimization, machine learning, deep learning, NLP, and XAI using Python librariesKey FeaturesLearn how to implement genetic algorithms using Python libraries DEAP, scikit-learn, and NumPyTake advantage of cloud computing technology to increase the performance of your solutionsDiscover bio-inspired algorithms such as particle swarm optimization (PSO) and NEATPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionWritten by Eyal Wirsansky, a senior data scientist and AI researcher with over 25 years of experience and a research background in genetic algorithms and neural networks, Hands-On Genetic Algorithms with Python offers expert insights and practical knowledge to master genetic algorithms. After an introduction to genetic algorithms and their principles of operation, you’ll find out how they differ from traditional algorithms and the types of problems...
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