Grokking Deep Learning, (Paperback)
CLP 59301
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What Stands Out
Product Details
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | January, 2019 |
| Pages | 336 |
| Reading level | Professional & Vocational |
| Subgenre | Data Science |
| Series title | No Series |
| Edition | 1 |
| Publisher | Manning Publications |
| Original languages | English |
| Language | English |
| Edu focus | Technology |
| Educational level | High School |
| Is collectible | N |
| Binding type | Perfect Binding |
| Digital file format | |
| Digital reader format | |
| Digital audio file format | |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.40 x 0.70 x 9.10 in (18.8 x 1.8 x 23.1 cm) |
| Assembled product weight | 1.2 lb (540 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
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Beginner Learners
Ideal for those new to deep learning, offering clear explanations and foundational concepts for understanding the subject.
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Self-Study Enthusiasts
Perfect for individuals who prefer self-paced learning with practical examples and exercises to enhance comprehension.
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Aspiring Data Scientists
Great for aspiring data scientists seeking to develop skills in deep learning and neural networks for career advancement.
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Advanced Practitioners
Not suitable for those with extensive experience, as the content may be too basic and not challenging enough.
Product Description
Grokking Deep Learning, (Paperback)
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Andrew Trask All Books Editorial Review
Grokking Deep Learning (Paperback) is an essential non-fiction resource for professionals and vocational learners in the field of computing and data science. Published by Manning Publications in January 2019, this 336-page book is meticulously designed to enhance understanding of deep learning concepts. With a perfect binding and dimensions of 7.40 x 0.70 x 9.10 inches, it is conveniently portable yet comprehensive. The book is written in English and tailored for those with a high school educational level, making it accessible to a wide audience eager to deepen their technical knowledge.
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Pros
- Comprehensive deep learning concepts covered thoroughly
- Perfect binding for durability and ease of use
- Well-suited for professionals in data science
- Designed for various digital formats including PDF
- Portable size for reading on the go
Cons
- Limited interactive features for digital readers
Platform Trust & Buyer Confidence
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CLP 59301
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