eBook - ePub

Hands-On Genetic Algorithms with Python

Name: Hands-On Genetic Algorithms with Python
Author: Eyal Wirsansky

Apply genetic algorithms to solve real-world AI and machine learning problems

Eyal Wirsansky,

418 pages
English
ePUB (mobile friendly)
Available on iOS & Android

eBook - ePub

Hands-On Genetic Algorithms with Python

Apply genetic algorithms to solve real-world AI and machine learning problems

Eyal Wirsansky,

About this book

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 libraries

Key Features

Learn how to implement genetic algorithms using Python libraries DEAP, scikit-learn, and NumPy
Take advantage of cloud computing technology to increase the performance of your solutions
Discover bio-inspired algorithms such as particle swarm optimization (PSO) and NEAT
Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Written 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 they can solve, followed by applying them to search and optimization tasks such as planning, scheduling, gaming, and analytics. As you progress, you'll delve into explainable AI and apply genetic algorithms to AI to improve machine learning and deep learning models, as well as tackle reinforcement learning and NLP tasks. This updated second edition further expands on applying genetic algorithms to NLP and XAI and speeding up genetic algorithms with concurrency and cloud computing. You'll also get to grips with the NEAT algorithm. The book concludes with an image reconstruction project and other related technologies for future applications. By the end of this book, you'll have gained hands-on experience in applying genetic algorithms across a variety of fields, with emphasis on artificial intelligence with Python.

What you will learn

Use genetic algorithms to solve planning, scheduling, gaming, and analytics problems
Create reinforcement learning, NLP, and explainable AI applications
Enhance the performance of ML models and optimize deep learning architecture
Deploy genetic algorithms using client-server architectures, enhancing scalability and computational efficiency
Explore how images can be reconstructed using a set of semi-transparent shapes
Delve into topics like elitism, niching, and multiplicity in genetic solutions to enhance optimization strategies and solution diversity

Who this book is for

If you're a data scientist, software developer, AI enthusiast who wants to break into the world of genetic algorithms and apply them to real-world, intelligent applications as quickly as possible, this book is for you. Working knowledge of the Python programming language is required to get started with this book.

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Yes, you can access Hands-On Genetic Algorithms with Python by Eyal Wirsansky in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.