Are you looking for the best deep neural networks ebooks? Based on expert reviews, we ranked them. We've listed our top-ranked picks, including the top-selling deep neural networks ebooks.
We Recommended:
- Amazon Kindle Edition
- Rashid, Tariq (Author)
- English (Publication Language)
- 04/16/2016 (Publication Date)
- Amazon Kindle Edition
- Saleh, Hyatt (Author)
- English (Publication Language)
- 332 Pages - 07/22/2020 (Publication Date) - Packt Publishing (Publisher)
- Amazon Kindle Edition
- Aggarwal, Charu C. (Author)
- English (Publication Language)
- 512 Pages - 08/25/2018 (Publication Date) - Springer (Publisher)
- Amazon Kindle Edition
- Nakamoto, Pat (Author)
- English (Publication Language)
- 07/01/2018 (Publication Date)
- Amazon Kindle Edition
- Heaton, Jeff (Author)
- English (Publication Language)
- 777 Pages - 05/17/2022 (Publication Date)
- Amazon Kindle Edition
- Gridin, Ivan (Author)
- English (Publication Language)
- 421 Pages - BPB Publications (Publisher)
- Amazon Kindle Edition
- Antiga, Luca Pietro Giovanni (Author)
- English (Publication Language)
- 519 Pages - 07/01/2020 (Publication Date) - Manning (Publisher)
- Amazon Kindle Edition
- Vasilev, Ivan (Author)
- English (Publication Language)
- 388 Pages - 01/16/2019 (Publication Date) - Packt Publishing (Publisher)
- Amazon Kindle Edition
- Adams, Anthony (Author)
- English (Publication Language)
- 287 Pages - 03/15/2020 (Publication Date)
- Amazon Kindle Edition
- Dawani, Jay (Author)
- English (Publication Language)
- 366 Pages - 06/12/2020 (Publication Date) - Packt Publishing (Publisher)
- Amazon Kindle Edition
- Klaas, Sebastian (Author)
- English (Publication Language)
- 376 Pages - BPB Publications (Publisher)
- Amazon Kindle Edition
- Ranjan, Sumit (Author)
- English (Publication Language)
- 334 Pages - 08/14/2020 (Publication Date) - Packt Publishing (Publisher)
- Amazon Kindle Edition
- Ekman, Magnus (Author)
- English (Publication Language)
- 752 Pages - 07/19/2021 (Publication Date) - Addison-Wesley Professional (Publisher)
- Amazon Kindle Edition
- Kim, Phil (Author)
- English (Publication Language)
- 229 Pages - 06/15/2017 (Publication Date) - Apress (Publisher)
- Amazon Kindle Edition
- Rothman, Denis (Author)
- English (Publication Language)
- 384 Pages - 01/29/2021 (Publication Date) - Packt Publishing (Publisher)
- Amazon Kindle Edition
- Gulli, Antonio (Author)
- English (Publication Language)
- 320 Pages - 04/26/2017 (Publication Date) - Packt Publishing (Publisher)
- Amazon Kindle Edition
- Rothman, Denis (Author)
- English (Publication Language)
- 564 Pages - 03/25/2022 (Publication Date) - Packt Publishing (Publisher)
- Amazon Kindle Edition
- Dedov, Florian (Author)
- English (Publication Language)
- 86 Pages - 02/24/2020 (Publication Date)
- Amazon Kindle Edition
- Weidman, Seth (Author)
- English (Publication Language)
- 253 Pages - 09/09/2019 (Publication Date) - O'Reilly Media (Publisher)
- Amazon Kindle Edition
- Beer, Wolfgang (Author)
- English (Publication Language)
- 104 Pages - 04/08/2021 (Publication Date)
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- Specifications: How powerful they are can be measured.
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FAQ:
Q: What is the best book for neural network design?
A: Neural Network Design (2nd Edition) This book, by the authors of the Neural Network Toolbox for MATLAB, provides a clear and detailed coverage of fundamental neural network architectures and learning rules.
Q: What is the purpose of this book Neural Networks and deep learning?
A: Neural Networks and Deep Learning This book teaches you about Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data. It also covers deep learning, a powerful set of techniques for learning in neural networks.
Q: What is a deep neural network?
A: (Neural networks can also extract features that are fed to other algorithms for clustering and classification; so you can think of deep neural networks as components of larger machine-learning applications involving algorithms for reinforcement learning, classification and regression .)
Q: What are the drawbacks of neural network books eBooks?
A: Some drawbacks of the books are that it cannot be used as a primary source of the education material. The book can be used as a reference and extra knowledge of the origin of the neural networks. This is one of the finest neural network books eBooks. The book introduces the innovative and advanced research in biocomputing.
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