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Item #:
143332282
Deep Learning with Python
86% of respondents would recommend this to a friend
Item #:
143332282
HTG 9170
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What Stands Out
Comprehensive Coverage
This book provides thorough insights into deep learning concepts, techniques, and applications, ensuring readers from beginners to advanced levels can understand and implement neural networks effectively.
Practical Examples
Includes hands-on examples and exercises, allowing readers to apply theories in real-world scenarios, which enhances understanding and retention of deep learning principles through practical application.
Expert Author
Written by a leading expert in the field, this resource offers authoritative insights and guidance, making it a valuable asset for anyone looking to deepen their knowledge of deep learning methodologies.
Product Details
- Printed in full color!
- Learn deep learning from first principles
- Cover topics like image classification, image segmentation, timeseries forecasting, and text classification
- Includes practical techniques for real-world applications
- Written by François Chollet, the creator of the Keras library
- Includes a comprehensive table of contents with 14 chapters
| Publisher | Manning Publications |
| Publication date | 7 April 2022 |
| Edition | 1st |
| Language | English |
| Print length | 400 pages |
| ISBN-10 | 1617296864 |
| ISBN-13 | 978-1617296864 |
| Item weight | 1.07 kg |
| Dimensions | 18.73 x 3.3 x 23.5 cm |
Who Should Buy?
-
Aspiring Data Scientists
This book offers a practical introduction to deep learning suitable for newcomers to data science and machine learning.
-
Software Developers
Developers looking to integrate deep learning into existing applications will find valuable insights and coding examples.
-
Academic Students
Ideal for university students studying machine learning or AI, providing a solid theoretical foundation paired with practical examples.
-
Beginner Programmers
Those without programming experience may struggle with the technical content and coding examples included in the book.
Product Description
Deep Learning with Python
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Customer Questions & Answers
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Question:
Do I need prior experience in machine learning to read this book?
Answer: No, the book is designed for readers with intermediate Python skills and no previous experience in Keras, TensorFlow, or machine learning is required. -
Question:
What topics are covered in this edition?
Answer: The book covers deep learning fundamentals, image classification, timeseries forecasting, text classification, and more. -
Question:
Is there any additional content included with the print book?
Answer: Yes, the purchase includes a free eBook in PDF, Kindle, and ePub formats.
AI & Machine Learning Editorial Review
Deep Learning With Python is an insightful guide for those venturing into the realms of neural networks and deep learning, specifically utilizing TensorFlow and Keras. It is well-structured, making the complex concepts accessible to readers with minimal mathematical background. The author effectively balances hands-on coding examples with deeper theoretical explanations, alleviating the potential intimidation often associated with rigorous mathematics. While familiarity with Python is necessary, the book is approachable for beginners willing to grasp essential programming constructs. Despite some critiques regarding the depth of explanation and reliance on informal language, many readers find it a valuable entry point to understanding deep learning.
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Pros
- Well-structured chapters for easier learning
- Clear and intuitive explanations provided
- Great resource for beginners in neural networks
- Balanced between theory and practical examples
- Good print quality and vivid illustrations
Cons
- Paper quality could be improved for durability
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HTG 9170
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Features & Benefits
- Revised edition of the bestselling 'Deep Learning with Python'.
- Learn from François Chollet, the creator of Keras.
- Practical techniques for real-world application.
- Complete coverage of deep learning concepts from first principles.
- Includes a free eBook with the purchase of the print book.
- Full-color printing enhances understanding with clear examples and illustrations.
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