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MATLAB Deep Learning: With Machine Learning, Neural Networks and Artificial Intelligence 1st ed. Edition
87% of respondents would recommend this to a friend
€ 49
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What Stands Out
Detaily produktu
| 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?
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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.
OPIS PRODUKTU
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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odpoveď: Nakupovať MATLAB Deep Learning: With Machine Learning, Neural online z Ubuy je jednoduché.. Musíte len vyhľadať produkt, vybrať spôsob dopravy pri pokladni a nechať si ho doručiť na miesto, kde sa nachádzate. -
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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
Zápory
- Some readers found the content to be shallow and lacking in substance
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