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Item #:
13422615
Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning
87% of respondents would recommend this to a friend
Item #:
13422615
XCD 98
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What Stands Out
Comprehensive Coverage
This tutorial offers an extensive examination of deep learning mathematics, making complex concepts accessible for beginners while providing in-depth insights for seasoned practitioners looking to enhance their knowledge.
Hands-On Approach
With practical examples and exercises, the book enables readers to apply mathematical concepts in real-world scenarios, enhancing their understanding of artificial intelligence and reinforcing learning through practice.
Expert Insights
Authored by industry professionals, this guide presents cutting-edge techniques and best practices in deep learning, equipping readers with essential skills to tackle current challenges in artificial intelligence development.
Product Details
| Publisher | Sebtel Press |
| Publication date | March 28, 2019 |
| Language | English |
| Print length | 216 pages |
| ISBN-10 | 0956372813 |
| ISBN-13 | 978-0956372819 |
| Item Weight | 11.4 ounces (323.19 grams) |
| Dimensions | 6 x 0.49 x 9 inches (15.2 x 1.2 x 22.9 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for those looking to build a foundational understanding of deep learning mathematics to enhance their analytical skills.
-
Computer Science Students
Useful for students wanting to supplement their curriculum with practical insights into deep learning applications and theories.
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AI Practitioners
Benefits professionals needing a refresher in the mathematical concepts crucial for developing and implementing AI models effectively.
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Complete Beginners
Not suitable for individuals with no prior knowledge of mathematics or deep learning, as it assumes some foundational concepts.
Product Description
Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning
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Intelligence & Semantics Editorial Review
Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning offers a foundational insight into deep learning mathematics. Readers have noted that this book is particularly well-suited for those with a basic math background who are newcomers to AI, helping them build a foundation for more complex material. However, some readers experienced confusion with mathematical terms and subscripts, especially in discussions of algorithms like backpropagation. Despite the challenges, many found the writing style engaging and appreciated the humor intertwined within technical explanations, making this book a unique tool for understanding AI concepts on a high level while still requiring further study for in-depth knowledge.
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Pros
- Engaging writing style with humor
- Great for beginners with some math background
- Covers essential deep learning concepts
- Readable and clear explanations
- Helps build a foundation for advanced studies
Cons
- Some concepts lack adequate definitions making understanding challenging
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