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Grokking Deep Learning teaches you to build deep learning neural networks from scratch!
Item #:
90328104
Grokking Deep Learning
87% of respondents would recommend this to a friend
Item #:
90328104
R$ 449
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What Stands Out
Comprehensive Guide
Offers a thorough exploration of deep learning concepts, making complex topics accessible for readers with varying expertise levels, from beginners to advanced practitioners.
Hands-On Approach
Emphasizes practical applications and real-world examples, allowing readers to effectively implement deep learning techniques and reinforce learning through active engagement.
Updated Content
Includes insights into the latest advancements in deep learning, ensuring readers stay current with industry trends and technologies, enhancing the book's relevance and applicability.
Product Details
- Introduces Artificial Intelligence and Deep Learning as revolutionary technologies
- Explains the behavior of neural networks based on human brains
- Suitable for readers with high school-level math and intermediate programming skills
- Covers building neural networks for image recognition, language translation, and gaming
- Provides insights into the impact of Deep Learning on various industries
- Includes guidance on understanding algorithms and the principles of Deep Learning
| Publisher | Manning Publications |
| Publication date | 22 May 2019 |
| Edition | 1st |
| Language | English |
| Print length | 336 pages |
| ISBN-10 | 1617293709 |
| ISBN-13 | 978-1617293702 |
| Item weight | 572 g |
| Dimensions | 18.75 x 1.78 x 23.5 cm |
Who Should Buy?
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Beginners in AI
Ideal for individuals new to artificial intelligence, offering clear explanations and foundational concepts in deep learning.
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Self-learners
Perfect for self-directed learners seeking a structured yet accessible approach to understanding deep learning principles.
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Educators and Tutors
Beneficial for teachers looking to incorporate deep learning concepts into their curriculum or enhance their instructional materials.
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Advanced Researchers
Less suitable for expert researchers, as it may not cover the latest advanced topics or cutting-edge research.
Product Description
Grokking Deep Learning
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Customer Questions & Answers
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Question:
What programming language is used in the book?
Answer: The book only uses Python and its math-supporting library, NumPy. -
Question:
Is the eBook version included with the print book purchase?
Answer: Yes, the purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. -
Question:
Who is the book suitable for?
Answer: The book is suitable for readers with high school-level math and intermediate programming skills.
Languages & Tools Editorial Review
** Grokking Deep Learning** "Grokking Deep Learning" has received a predominantly positive reception from readers, particularly for its accessibility and engaging writing style. Many users praise Andrew's ability to distill complicated concepts into simpler, more digestible pieces, making the subject of deep learning approachable even for those without a strong foundation in mathematics or computer science. Readers have reported enjoying the process of learning, with some stating that the book has become their primary resource for understanding deep learning while supplementing other courses. The book’s format and example-driven content have reportedly made it both enjoyable and practical for learners. However, not all feedback has been favorable. One reviewer expressed disappointment, arguing that the book lacks sufficient mathematical depth, which they felt was critical to grasping the subject fully. They criticized certain explanations for being overly simplistic and not providing a strong conceptual foundation. Despite this, others found the writing clear, enjoyable, and motivating, leading them to explore the field further. On balance, "Grokking Deep Learning" stands out as an informative and engaging introduction to deep learning, particularly suitable for beginners or those with non-technical backgrounds. The book has inspired many to delve deeper into the subject, making it a notable entry in the field. **
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Pros
- Simplifies complex deep learning concepts.
- Accessible for beginners and non-technical readers.
- Engaging and enjoyable writing style.
- Practical examples and exercises.
Cons
- Some readers find the mathematical explanations lacking depth.
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Features & Benefits
- Learn to build deep learning neural networks from scratch
- Teaches you the science behind neural network training
- Only uses Python and NumPy library
- Suitable for readers with high school-level math and intermediate programming skills
- Includes a free eBook with the purchase of print book
- Introduces readers to federated learning
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