With Hands-On Genetic Algorithms with Python, explore the ins and outs of genetic algorithms with this fast-paced guide. Implement tasks such as feature selection, search optimization, and cluster analysis using Python. (Limited-time offer)
Book Description
- Section 1: The Basics of Genetic Algorithms
- An Introduction to Genetic Algorithms
- Understanding the Key Components of Genetic Algorithms
- Section 2: Solving Problems with Genetic Algorithms
- Using the DEAP Framework
- Combinatorial Optimization
- Constraint Satisfaction
- Optimizing Continuous Functions
- Section 3: Artificial Intelligence Applications of Genetic Algorithms
- Enhancing Machine Learning Models Using Feature Selection
- Hyperparameter Tuning of Machine Learning Models
- Architecture Optimization of Deep Learning Networks
- Reinforcement Learning with Genetic Algorithms
- Section 4: Related Technologies
- Genetic Image Reconstruction
- Other Evolutionary and Bio-Inspired Computation Techniques
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Author(s): Eyal Wirsansky
Publisher: Packt Publishing
Published: January 31, 2020
Format(s): Online
File size: –
Number of pages: 346
Download / View Link(s): This offer has ended.
Free as of07/04/2020 09/22/2020.
Publisher: Packt Publishing
Published: January 31, 2020
Format(s): Online
File size: –
Number of pages: 346
Download / View Link(s): This offer has ended.
Free as of