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49266543
Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks Paperback
Item #:
49266543
XPF 6461
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By the end of this book, you'll have built a strong foundation in neural networks and deep learning mathematical concepts.
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What Stands Out
Foundational Skills
Provides essential mathematical concepts critical for understanding and optimizing deep learning models, allowing readers to build robust knowledge for future advancements in AI.
Practical Approach
Integrates hands-on exercises that reinforce learning through practical applications, enabling readers to implement complex mathematics directly into real-world deep learning scenarios.
Accessible Format
Written in an easy-to-understand style, making advanced mathematical topics approachable for beginners and professionals, fostering a deeper understanding of neural networks.
Product Details
| Language | English |
| Publisher | Packt Publishing |
| Book Format | Paperback |
| Original Languages | English |
| Number of Pages | 364 |
| Author | Jay Dawani |
| Title | Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks |
| ISBN-13 | 9781838647292 |
| Publication Date | June, 2020 |
| ISBN-10 | 1838647295 |
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Education |
| Pub date | 2020-06-12 |
| Pages | 364 |
| Subgenre | Computers |
| Edition | Standard Edition |
| Original languages | English |
| Item Weight | 1 lbs (450 grams) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for beginners looking to understand the mathematical concepts essential for building deep learning models.
-
Students in STEM
Perfect for university students in scientific fields who require mathematical skills in machine learning and neural networks.
-
Professionals Upskilling
Great for professionals seeking to enhance their skills in machine learning and deepen their mathematical understanding.
-
Complete Beginners
Not suitable for users with no prior knowledge of mathematics or deep learning concepts.
Product Description
Hands-On Mathematics for Deep Learning: Build a solid mathematical foundation for training efficient deep neural networks Paperback
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Pros
- Clear explanations of complex topics
- Practical examples for better understanding
- Comprehensive coverage of essential math
- Great for beginners and experienced learners
- Well-structured and easy to follow
Cons
- Some sections may be too detailed for quick reference.
Product Price History
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Features & Benefits
- Build a solid mathematical foundation for deep neural networks.
- Understand core concepts like linear algebra, calculus, and gradient algorithms.
- Learn to apply deep learning to vision, image, text, and sequence problems.
- Gain insights into optimization techniques and neural network architectures.
- Use Python libraries to bridge the gap between math and implementation.
- Perfect for data scientists and aspiring deep learning developers.
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