Deep learning is driving the AI revolution, and Py Torch is making it easier than ever before for anyone to build deep learning applications. This Py Torch book will help you uncover expert techniques to get the most out of your data and build complex neural network models.
The book starts with a quick overview of Py Torch and explores using convolutional neural network (CNN) architectures for image classification. You’ll then work with recurrent neural network (RNN) architectures and transformers for sentiment analysis. As you advance, you’ll apply deep learning across different domains, such as music, text, and image generation using generative models and explore the world of generative adversarial networks (GANs). You’ll not only build and train your own deep reinforcement learning models in Py Torch but also deploy Py Torch models to production using expert tips and techniques. Finally, you’ll get to grips with training large models efficiently in a distributed manner, searching neural architectures effectively with Auto ML, and rapidly prototyping models using Py Torch and fast.ai.
By the end of this Py Torch book, you’ll be able to perform complex deep learning tasks using Py Torch to build smart artificial intelligence models.
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