Marketplace.
Neural Networks & Deep Learning
£51.67
£51.67/each
Sold and sent by Speedyhen
Delivered by post or courier
FREE standard delivery on this product
Find out more about Marketplace
Neural Networks & Deep Learning
£51.67
£51.67/each
Description
This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Deep learning methods for various data domains, such as text, images, and graphs are presented in detail. The chapters of this book span three categories: The basics of neural networks: The backpropagation algorithm is discussed in Chapter 2.Many traditional machine learning models can be understood as special cases of neural networks. Chapter 3 explores the connections between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 4 and 5. Chapters 6 and 7 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 8, 9, and 10 discuss recurrent neural networks, convolutional neural networks, and graph neural networks. Several advanced topics like deep reinforcement learning, attention mechanisms, transformer networks, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 11 and 12. The textbook is written for graduate students and upper under graduate level students. Researchers and practitioners working within this related field will want to purchase this as well.Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.The second edition is substantially reorganized and expanded with separate chapters on backpropagation and graph neural networks. Many chapters have been significantly revised over the first edition.Greater focus is placed on modern deep learning ideas such as attention mechanisms, transformers, and pre-trained language models.
Sold by Speedyhen (Speedy Hen LTD)
| Author | Aggarwal Charu C. |
|---|---|
| ISBN-13 | 9783031296413 |
| Item Height | 3.8 |
| Item Length | 18.4 |
| Item Width | 26.2 |
| Publisher | Springer (pod) |
Delivery
Here are your delivery options from this Marketplace partner:
Standard delivery - arrives in 3-4 working days
- FREE on this product sent by this partner
Standard returns
Not happy with a Marketplace item? You can request a return and refund online up to 30 days after the delivery date. You'll need to return the item to the Marketplace partner.Our returns policy
About Marketplace
We're giving you more choice than ever before. Shop more products from more brands across homewares, beauty, electricals and much more.
And all delivered from our partners right to your door.
No reviews yet
Help other customers like you
Reviews are submitted by our customers directly through our website. We also share reviews from other retailers' websites to help you make an informed decision.
Write a review