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Can I read Deep Learning with Python : Learn Best Practices of Deep Learning Models with PyTorch on EtoBox?
Deep Learning with Python : Learn Best Practices of Deep Learning Models with PyTorch by Nikhil Ketkar & Jojo Moolayil is a nonfiction available to read on EtoBox.
What is Deep Learning with Python : Learn Best Practices of Deep Learning Models with PyTorch about?
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebooks Artificial Intelligence Research Group. You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks, recurrent neural networks, long short-term memory networks, autoencoders and gene
Who reads Deep Learning with Python : Learn Best Practices of Deep Learning Models with PyTorch?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Nikhil Ketkar & Jojo Moolayil
- Publisher
- Apress Publications
- Published
- 2023
- Language
- EN
- ISBN
- 9781484253632
- Category
- nonfiction
- Subjects
- Computer Science, Mathematics, Language Learning
- Updated
- 2026-03-24
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