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Math and Architectures of Deep Learning: A Primer for Computer Vision, Natural Language Processing, and Speech Recognition
$20.40
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- A comprehensive guide to the mathematical foundations and architectural principles of deep learning.
- Covers topics such as linear algebra, probability theory, optimization, and neural networks.
- Provides detailed explanations of different deep learning architectures, including convolutional neural networks, recurrent neural networks, and transformers.
- Includes practical examples and exercises to help readers apply the concepts to real-world problems.
- Suitable for students, researchers, and practitioners in the field of deep learning.
Condition: New original from publisher
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