Independently published, 2021. — 1187 p. Version 1.0, 2021-05-18. If you're looking for a book where you can learn about Deep Learning and PyTorch without having to spend hours deciphering cryptic text and code, and that's easy and enjoyable to read, this is it :-). The book covers the basics of gradient descent up to fine-tuning large NLP models (BERT and GPT-2) using...
Packt Publishing Ltd., 2020. — 301 p. —ISBN: 978-1-78953-051-3. Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models With continuously evolving research and development, Generative Adversarial Networks (GANs) are the next big thing in the field of deep learning. This book highlights the key improvements in GANs...
Packt Publishing, 2019. — 254 p. — ISBN: 978-1-78980-459-1. Implement techniques such as image classification and natural language processing (NLP) by understanding the different neural network architectures Machine learning is rapidly becoming the most preferred way of solving data problems, thanks to the huge variety of mathematical algorithms that find patterns, which are...
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