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32224869
PyTorch Pocket Reference: Building and Deploying Deep Learning Models
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Artikal br.:
32224869
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What Stands Out
Concise Guide
A compact reference that provides essential information on PyTorch, ideal for quickly building and deploying deep learning models without overwhelming detail, making it perfect for beginners and busy professionals.
Hands-On Approach
Includes practical examples and real-world applications, enabling users to immediately implement learned concepts, thus enhancing understanding and retention of deep learning techniques.
Updated Content
Current with the latest PyTorch developments, this edition ensures users are working with the most up-to-date tools and practices, giving them a competitive edge in the rapidly evolving field of deep learning.
Detalji o proizvodu
| Publisher | O'Reilly Media |
| Publication date | June 15, 2021 |
| Edition | 1st |
| Language | English |
| Print length | 307 pages |
| ISBN-10 | 149209000X |
| ISBN-13 | 978-1492090007 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 4.25 x 0.65 x 7 inches (10.8 x 1.7 x 17.8 cm) |
Who Should Buy?
-
Beginner Developers
Ideal for newcomers to deep learning looking for a concise guide to start building models using PyTorch.
-
Busy Professionals
Perfect for data scientists and ML engineers who need a quick reference for PyTorch without extensive reading.
-
Rapid Prototypers
Beneficial for those requiring swift model development and deployment, providing essential insights without overwhelming detail.
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Comprehensive Learners
Not suitable for those who prefer in-depth study and theoretical understanding of deep learning concepts.
OPIS PROIZVODA
PyTorch Pocket Reference: Building and Deploying Deep Learning Models
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Intelligence & Semantics Editorial Review
PyTorch Pocket Reference: Building and Deploying Deep Learning Models is an informative guide published by O'Reilly Media on June 15, 2021. It covers essential aspects of using PyTorch, a dominant framework in machine learning research. Users have found the book useful for quickly referencing key concepts and API subsets without getting lost in extensive online documentation. The content succinctly addresses optimization loops and usage guidance, allowing for effective application in development. However, some readers note the challenges of reproducibility due to missing requirements files and the reliance on external tutorials for deeper understanding, indicating a need for improved clarity and completeness.
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Pros
- Concise guide for quick reference
- Helpful for beginners in PyTorch
- Well-categorized API subsets
- Clear writing style and perspective
- Informative for transitioning from other frameworks
Cons
- Some content may feel incomplete or outdated
Product Price History
Važna informacija
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Karakteristike i prednosti
- PyTorch enables significant advances in deep learning and AI
- The book is suitable for both beginners and advanced users in machine learning and AI.
- Written for those interested in exploring PyTorch with examples and detailed explanations.
- Helps beginners learn basics, introduces PyTorch API to users of other frameworks, and covers advanced topics for experienced users.
- The author aims to provide a comprehensive resource for learning and mastering PyTorch.
- The book addresses the need for a resource with high-level overviews and detailed examples.
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