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20265583
MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence 1st ed. Edition
87% of respondents would recommend this to a friend
Item #:
20265583
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What Stands Out
Comprehensive Learning
This book offers a thorough understanding of deep learning concepts, integrating machine learning, neural networks, and AI to equip readers with essential skills and practical knowledge for real-world applications.
Hands-on Examples
Packed with practical examples and MATLAB code snippets, the book enables readers to apply theoretical knowledge, fostering a deeper understanding of complex concepts in deep learning and AI development.
Expert Insights
Authored by industry professionals, the book provides insider tips and insights, enhancing the learning experience and offering valuable perspectives on current trends and best practices in deep learning.
Product Details
| Publisher | Apress |
| Publication date | June 15, 2017 |
| Edition | 1st ed. |
| Language | English |
| Print length | 168 pages |
| ISBN-10 | 1484228448 |
| ISBN-13 | 978-1484228449 |
| Item Weight | 12.5 ounces (354.38 grams) |
| Dimensions | 6.1 x 0.39 x 9.25 inches (15.5 x 1 x 23.5 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for beginners who want to learn deep learning concepts and apply them using MATLAB effectively.
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Research Professionals
Perfect for researchers needing advanced tools for neural networks and AI in their computational studies.
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Educators in Tech
Great resource for educators teaching deep learning, providing structured content and practical MATLAB examples.
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Beginner Programmers
Not suitable for complete novices without prior programming experience, as it assumes familiarity with basic coding.
Product Description
MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence 1st ed. Edition
About This Item
Introducing the 1st Edition of "MATLAB Deep Learning: With Machine Learning, Neural Networks, and Artificial Intelligence" Are you ready to delve into the exciting world of deep learning and artificial intelligence? Look no further than "MATLAB Deep Learning," a comprehensive primer that will take you from the fundamentals of machine learning to the intricacies of neural networks and convolutional neural networks. Using MATLAB as the underlying programming language, this book combines theory with practical applications to provide you with a solid understanding of deep learning. Whether you're tackling big data, building smart bots, or solving complex data problems, this book will equip you with the right tools and knowledge. Written by Phil Kim, a seasoned MATLAB programmer and user, this book draws on his expertise in AI and machine learning. With his experience at the Korea Aerospace Research Institute and the National Rehabilitation Research Institute of Korea, he brings real-world insights to the table. Here's what you can expect from "MATLAB Deep Learning": 1.
Use MATLAB for deep learning: Dive into MATLAB, the powerful programming language, and harness its capabilities for deep learning projects. 2. Discover neural networks: Gain a solid understanding of the fundamentals of neural networks and how they can be applied to real-world scenarios. 3. Work with convolution and pooling layers: Explore the complexities of convolutional neural networks and learn how to effectively use convolution and pooling layers. 4.
Build a MNIST example: Put your newfound knowledge into practice by building a MNIST example using the concepts and techniques learned in the book. "MATLAB Deep Learning" is the ultimate guide for anyone seeking to unlock the potential of deep learning and AI. With its blend of theory and practical examples, this book will empower you to tackle modern data analysis challenges and create intelligent solutions. Don't miss out on this opportunity to become a proficient deep learning practitioner. Order your copy of "MATLAB Deep Learning: With Machine Learning, Neural Networks, and Artificial Intelligence" today.
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Product Buying Guide
The MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence 1st ed. Edition offers an in-depth primer on MATLAB for deep learning and AI. This book provides a comprehensive approach, starting with machine learning fundamentals and progressing to neural networks, deep learning, and convolutional neural networks using MATLAB as the underlying programming language. The author, Phil Kim, PhD, brings extensive experience in MATLAB programming, AI, and machine learning, making this book an invaluable resource for those interested in tackling real-world big data and complex data problems.
Product Specifications
- Title: MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence 1st ed. Edition
- Programming Language: MATLAB
- Author: Phil Kim, PhD
- Publisher: Apress; 1st ed. edition (March 5, 2019)
- Paperback: 366 pages
- ISBN-10: 1484234682
- ISBN-13: 978-1484234687
Key Features
- Covers machine learning fundamentals, neural networks, and deep learning
- Uses MATLAB for examples and case studies
- Provides insights into handling real-world big data and complex data problems
- Author brings extensive MATLAB programming and AI experience
Usage Scenarios
- Ideal for individuals interested in deep learning and AI using MATLAB
- Suitable for professionals working with big data, smart bots, and complex data problems
- Beneficial for students and researchers exploring neural networks and multi-layer neural networks
Some User Review
- The MATLAB Deep Learning book has been instrumental in enhancing my understanding of deep learning concepts using MATLAB. The examples and case studies are insightful and practical, making the learning experience rewarding.
- As a professional working with complex data problems, this book has provided valuable techniques and applications for tackling real-world challenges. The author's expertise in MATLAB programming and AI shines through the content, making it a highly recommended resource.
Competitors
The price of the book is competitive and offers great value considering the depth of content and the author's expertise. It is reasonably priced compared to other similar resources in the market, making it an attractive investment for those seeking in-depth knowledge of MATLAB for deep learning and AI.
Buying Considerations
- Consider the proficiency in MATLAB programming and the level of familiarity with deep learning and AI concepts to fully leverage the content of this book
- Evaluate the current need for understanding and applying deep learning in real-world scenarios to determine the immediate relevance of this resource
Conclusion
In conclusion, the MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence 1st ed. Edition is an indispensable guide for individuals and professionals looking to delve into the intricacies of deep learning and AI using MATLAB. With comprehensive coverage and practical insights, this book equips readers with the knowledge and techniques necessary to address modern data challenges effectively.
View LessThe MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence 1st ed. Edition offers an in-depth primer on MATLAB for deep learning and AI. This book provides a comprehensive approach, starting with machine learning fundamentals and progressing to neural networks, deep learning, and convolutional neural networks using MATLAB as the underlying programming language. The author, Phil Kim, PhD, brings extensive experience in MATLAB programming, AI, and machine learning, making this book an invaluable resource for those interested in tackling real-world big data and complex data problems. Continue Reading
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Intelligence & Semantics Editorial Review
The "MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence" book has received mixed feedback from customers. Some users found it to be a useful and concise guide for those with basic ML knowledge, hailing it as an excellent resource and recommending it to anyone looking to delve into the subject. They appreciated the hands-on experience the MATLAB source codes provided. However, other reviewers were greatly disappointed, finding the book to be shallow and lacking in substance, with some criticizing its content as a "fraud" and noting that it didn't offer any real knowledge. One user even mentioned that the chapter on convolutional networks lacked a definition of convolution, contributing to their dissatisfaction with the book.
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Pros
- Concise guide for understanding the concepts of machine learning and deep learning
- Provides hands-on experience through MATLAB source codes
- Recommended for those with basic ML knowledge
Cons
- Some readers found the content to be shallow and lacking in substance
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