Advanced Deep Learning with Python
Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch
|Price||$44.99 - $60.12
|Format||Paper book / ebook (PDF)|
In order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application.
You'll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you'll focus on variational autoencoders and GANs. You'll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you'll use graph neural networks for processing structured data, along with covering meta-learning, which allows you to train neural networks with fewer training samples. Finally, you'll understand how to apply deep learning to autonomous vehicles.
By the end of this book, you'll have mastered key deep learning concepts and the different applications of deep learning models in the real world.
by Nihkil Ketkar
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This new 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 Faceboo...
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by Rowel Atienza
Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised for TensorFlow 2.x, this edition introduces you to the practical side of deep learning with new chapters on unsupervised learning using mutual informa...
Price: $39.99 | Publisher: Packt Publishing | Release: 2020
by Francois Chollet
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by Dipanjan Sarkar, Raghav Bali, Tamoghna Ghosh
Transfer learning is a machine learning (ML) technique where knowledge gained during training a set of problems can be used to solve other similar problems.The purpose of this book is two-fold; firstly, we focus on detailed coverage of deep learning (DL) and transfer learning, comparing and contrasting the two with easy-to-follow concepts...
Price: $44.99 | Publisher: Packt Publishing | Release: 2018
by Santanu Pattanayak
Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own.Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and depl...
Price: $4.99 | Publisher: Apress | Release: 2017
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Price: $39.99 | Publisher: Manning | Release: 2018
by Navin Kumar Manaswi
Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Appli...
Price: $39.99 | Publisher: Apress | Release: 2018