Book

Deep Learning with PyTorch

This book provides the intuition behind the state of the art Deep Learning architectures such as ResNet, DenseNet, Inception, and encoder-decoder without diving deep into the math of it. It shows how you can implement and use various architectures to solve problems in the area of image classification, language translation and NLP using PyTorch.

Offered byPackt Logo

Difficulty Level

Intermediate

Completion Time

8h44m

Language

English

About Book

Who Is This Book For?

This book is for machine learning engineers, data analysts, data scientists interested in deep learning and are looking to explore implementing advanced algorithms in PyTorch. Some knowledge of machine learning is helpful but not a mandatory need. Working knowledge of Python programming is expected.

Book content

chapters 8h44m total length

Getting Started with Pytorch for Deep Learning

Mathematical building blocks of Neural Networks

Getting Started with Neural Networks

Fundamentals of Machine Learning

Deep Learning for Computer Vision

Natural Language Processing for PyTorch

Advanced neural network architectures

Generative networks

Conclusion

Related Resources

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