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Item #:
4552526
Genetic Algorithms with Python
87% of respondents would recommend this to a friend
Item #:
4552526
HKD 235
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What Stands Out
Comprehensive Coverage
This book offers an in-depth exploration of genetic algorithms, making complex concepts accessible for both beginners and experienced practitioners, thereby facilitating a deeper understanding of optimization strategies.
Practical Implementation
Includes practical Python code examples, allowing readers to directly apply genetic algorithms to real-world problems, which enhances learning and eases the transition from theory to practice.
Well-Structured Approach
The structured layout guides readers through foundational theories to advanced applications, ensuring a progressive learning experience that builds confidence and competence in using genetic algorithms effectively.
Product Details
- Hands-on introduction to machine learning with genetic algorithms using Python
- Step-by-step tutorials for building skills from basic to advanced genetic programming
- Prepares readers to apply genetic algorithms to problems in their field of expertise
- Written by a polyglot programmer with over 15 years of experience
- Author's approach to learning new programming languages through solving familiar problems
| Publisher | CreateSpace Independent Publishing Platform |
| Publication date | April 29, 2016 |
| Language | English |
| Print length | 423 pages |
| ISBN-10 | 1540324001 |
| ISBN-13 | 978-1540324009 |
| Item Weight | 2.3 pounds (1.04 kg) |
| Dimensions | 7.44 x 0.96 x 9.69 inches (18.9 x 2.4 x 24.6 cm) |
Who Should Buy?
-
Beginner Programmers
Ideal for those new to genetic algorithms and Python, providing clear explanations and practical examples.
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Data Scientists
Useful for data analysis and optimization tasks, offering insight into evolutionary algorithms within data science contexts.
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Researchers
Beneficial for academic researchers exploring advanced computational techniques, featuring thorough explanations and in-depth applications.
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Advanced Experts
May lack depth for seasoned practitioners looking for cutting-edge techniques in genetic algorithms.
Product Description
Genetic Algorithms with Python
About This Item
Introducing Genetic Algorithms with Python, the ultimate tool for those seeking advanced optimization solutions. Harness the power of Python with this comprehensive library for Genetic Algorithms. Designed to streamline complex optimization problems, this package offers a user-friendly interface and a wealth of functionality.
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Whether you are analyzing large datasets or searching for the best parameters, this tool is the missing piece in your optimization puzzle. Don't waste any more time searching for the perfect optimization solution. With our Genetic Algorithm optimization in Python, you'll have the power to solve complex problems and achieve exceptional results. Upgrade your optimization capabilities today with Genetic Algorithms with Python. Experience the power of Python programming combined with the efficiency of Genetic Algorithms.
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Genetic Editorial Review
In this book, "Genetic Algorithms with Python," the author, Clinton Sheppard, provides a hands-on approach to learning Python and genetic algorithms. The book is lauded for its interesting problems and well-written code that gradually increases in complexity. It covers classic genetic algorithm problems like the 8 Queens Puzzle, Magic Squares, and Sudoku, making it a valuable resource. The book is suitable for intermediate programmers looking to delve into using genetic algorithms to solve puzzles and problems, with all the code available in the appendix and online. The book's clear writing and enjoyable examples make it easy to read, offering a more accessible introduction to genetic algorithms compared to more rigorous texts. However, some readers find the use of the `unittest` module for running genetic algorithms makes the code difficult to read and work with, preferring a different approach. While some readers find the book informative and a good starting point for learning genetic algorithms, others criticize it for its extensive and idiosyncratic Python code that can be off-putting. They find the focus on the Python programming environment challenging, particularly for those not familiar with object-oriented programming. Overall, "Genetic Algorithms with Python" is praised for its practical approach and valuable content, but it also receives criticism for its code-intensive nature and lack of broader conceptual explanations of genetic algorithms.
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Pros
- Hands-on approach to learning Python and genetic algorithms
- Interesting problems with well-written code
- Valuable resource for classic genetic algorithm problems
- Clear writing and enjoyable examples
Cons
- Use of the `unittest` module makes code difficult to read for some
Product Price History
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HKD 235
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Features & Benefits
- Step-by-step tutorials for genetic algorithms
- Prepares for implementing genetic algorithms to problems in user's field
- Helps to learn a new programming language by applying genetic algorithms as a familiar problem
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