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Hands-On Simulation Modeling with Python: Develop simulation models for improved efficiency and precision in the decision-making process, 2nd Edition
86% of respondents would recommend this to a friend
HKD 528
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This book is your comprehensive and hands-on guide to understanding various computational statistical simulations using Python.
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產品詳情
- Learn how to construct state-of-the-art simulation models with Python
- Understand various statistical and physical simulations to improve systems using Python
- Create and analyze the numerical prototype of a real model using hands-on examples
- Evaluate performance and output results based on real-world scenarios
- Ideal for data scientists, simulation engineers, and individuals familiar with computational methods
- Covers topics such as Monte Carlo simulations, Markov Decision Processes, and resampling methods
| Publisher | Packt Publishing |
| Publication date | November 30, 2022 |
| Edition | 2nd ed. |
| Language | English |
| Print length | 460 pages |
| ISBN-10 | 1804616885 |
| ISBN-13 | 978-1804616888 |
| Item Weight | 1.73 pounds (780 grams) |
| Dimensions | 7.5 x 1.04 x 9.25 inches (19.1 x 2.6 x 23.5 cm) |
Who Should Buy?
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Data Scientists
Ideal for data scientists looking to build simulation models for data analysis and decision-making improvements.
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Operations Managers
Operations managers can enhance their problem-solving skills through simulation modeling techniques taught in the book.
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Students in STEM
Students pursuing science, technology, engineering, or mathematics will find practical applications of simulation modeling in this resource.
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Beginners in Python
Total beginners in Python may struggle with concepts and implementations detailed in the book without prior knowledge.
產品敘述
Hands-On Simulation Modeling with Python: Develop simulation models for improved efficiency and precision in the decision-making process, 2nd Edition
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Intelligence & Semantics Editorial Review
Hands-On Simulation Modeling with Python is a valuable resource for anyone interested in developing simulation models for improved efficiency and precision in the decision-making process. The book provides a comprehensive guide to using Python for simulation modeling, covering various techniques and tools. The author's hands-on approach and clear explanations make it easy for readers to understand and apply the concepts. The book also includes numerous examples and case studies that offer practical insights and real-world applications. Overall, this 2nd edition is a must-read for professionals and students in fields such as operations research, supply chain management, and industrial engineering.
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優點
- Comprehensive guide to using Python for simulation modeling
- Clear explanations and hands-on approach make it easy to understand
- Numerous examples and case studies for practical insights
- Suitable for professionals and students in various fields
缺點
- None mentioned in the review
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特色和優勢
- Develop simulation models with Python
- Construct numerical prototypes of real models
- Deep dive into various numerical simulation algorithms
- Create and analyze digital prototypes of physical models
- Learn to evaluate performance and output results based on how the prototype would work in the real world
- Simulate random walks using Markov chains
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