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Mastering PyTorch. Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond - Second Edition

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Mastering PyTorch. Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond - Second Edition Ashish Ranjan Jha - okladka książki

Mastering PyTorch. Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond - Second Edition Ashish Ranjan Jha - okladka książki

Serie wydawnicze:
Learning
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
558
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     ePub

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Do przechowalni

PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch deep learning book will help you uncover expert techniques to get the most out of your data and build complex neural network models.
You’ll build convolutional neural networks for image classification and recurrent neural networks 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, including diffusion models. You'll not only build and train your own deep reinforcement learning models in PyTorch but also learn to optimize model training using multiple CPUs, GPUs, and mixed-precision training. You’ll deploy PyTorch models to production, including mobile devices. Finally, you’ll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep learning toolbelt, teaching you how to use fastai to prototype models and PyTorch Lightning to train models. You’ll discover libraries for AutoML and explainable AI (XAI), create recommendation systems, and build language and vision transformers with Hugging Face.
By the end of this book, you'll be able to perform complex deep learning tasks using PyTorch to build smart artificial intelligence models.

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O autorze książki

Ashish Ranjan Jha received his bachelor's degree in electrical engineering from IIT Roorkee (India), a master's degree in Computer Science from EPFL (Switzerland), and an MBA degree from Quantic School of Business (Washington). He has received a distinction in all 3 of his degrees. He has worked for large technology companies, including Oracle and Sony as well as the more recent tech unicorns such as Revolut, mostly focused on artificial intelligence. He currently works as a machine learning engineer.

Ashish has worked on a range of products and projects, from developing an app that uses sensor data to predict the mode of transport to detecting fraud in car damage insurance claims. Besides being an author, machine learning engineer, and data scientist, he also blogs frequently on his personal blog site about the latest research and engineering topics around machine learning.

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