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Learning Genetic Algorithms with Python: Empower the performance of Machine Learning and AI models with the capabilities of a powerful search algorithm (English Edition) free ebook download

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Python

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Catalogue

Author(s):	Ivan Gridin

Date:	2021	Format:	epub	Language:	English	ISBN/ASIN:	8194837758
Pages:	270	OCR:		Quality:		ISBN13:
Uploader:	gestalt	Upload Date:	11/23/2021 8:15:59 AM

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Refuel your AI Models and ML applications with High-Quality Optimization and Search Solutions

Key Features
Complete coverage on practical implementation of genetic algorithms.
Intuitive explanations and visualizations supply theoretical concepts.
Added examples and use-cases on the performance of genetic algorithms.
Use of Python libraries and a niche coverage on the performance optimization of genetic algorithms.

Genetic algorithms are one of the most straightforward and powerful techniques used in machine learning. This book Learning Genetic Algorithms with Python guides the reader right from the basics of genetic algorithms to its real practical implementation in production environments.
Each of the chapters gives the reader an intuitive understanding of each concept. You will learn how to build a genetic algorithm from scratch and implement it in real-life problems. Covered with practical illustrated examples, you will learn to design and choose the best model architecture for the particular tasks. Cutting edge examples like radar and football manager problem statements, you will learn to solve high-dimensional big data challenges with ways of optimizing genetic algorithms.

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	Title	Link	Password	Size (MB)	Thank to	Inform Admin
3053253	Book	https://k2s.cc/file/d6fcdd57c3281/819483...		0.00	gestalt

Tags: algorithm Algorithms capabilities Empower English Genetic Learning Machine models performance

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Learning Genetic Algorithms with Python: Empower the performance of Machine Learning and AI models with the capabilities of a powerful search algorithm (English Edition) free ebook download

Category: Python

Description: Click to see full description

Category:
Python