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Mathematical Foundations of Deep Learning PDF – Xiaojing Ye
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About Mathematical Foundations of Deep Learning
Demystifying artificial intelligence requires a deep dive into vector calculus, linear algebra, and probability theory. In Mathematical Foundations of Deep Learning, Xiaojing Ye provides a rigorous mathematical breakdown of optimization algorithms and neural network convergence. The textbook bridges pure mathematics with practical deep learning frameworks. Graduate students and researchers reading the PDF version will gain theoretical clarity on gradient descent, loss landscapes, and generalization bounds.
Book Information
| 📖 Book Name: | Mathematical Foundations of Deep Learning |
| ✍️ Author: | Xiaojing Ye |
| 📁 Category: | Mathematics, Machine Learning, Data Science, Textbooks, English |
| 📄 File Type: | |
| 🌍 Language: | English |
About the Author
Xiaojing Ye is a Mathematics and Data Science Professor whose research focuses on mathematical optimization, signal processing, and theoretical machine learning.