Packt Publishing, 2018. — 272 p. — ISBN: 1788837991. Dive deeper into neural networks and get your models trained, optimized with this quick reference guide. Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It...
Manning Publications, 2020. — 560 p. — ISBN: 978-1-617296-17-8. Code files only! Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL...
Packt Publishing, 2018. — 334 p. Code files only! A hands-on guide to deep learning thats filled with intuitive explanations and engaging practical examples Key Features Designed to iteratively develop the skills of Python users who dont have a data science background Covers the key foundational concepts youll need to know when building deep learning systems Full of...
Packt, 2019. — 612 p. — ISBN: 9781838642709. !Code files only Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features Get to grips with the fundamentals of deep learning and neural networks Use R 3.5 and its libraries and APIs to build deep learning models for computer vision and text processing Implement effective deep...
2nd edition. — Apress, 2021. — 316 p. — ISBN: 978-1484253632. Code files only! 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...
Apress, 2017. — 169 p. — ISBN: 978-1-4842-2765-7. Code files only! Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of...
Fullstack.io, 2020. — 769 p. Code files only! Zero to Deep Learning is carefully designed to teach you step-by-step how to build, train, evaluate, improve and deploy deep learning models. Each chapter covers a topic and we provide full code examples as executable Jupyter notebooks. Within the first few minutes, we’ll know enough deep learning to start seeing the benefits of...
Packt Publishing, 2018. — 284 p. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and...
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