Deep Learning with PyTorch 1.x - Second Edition

1 (1 reviews total)
By Laura Mitchell , Sri. Yogesh K. , Vishnu Subramanian
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  1. Section 1: Building Blocks of Deep Learning with PyTorch 1.x

About this book

PyTorch is gaining the attention of deep learning researchers and data science professionals due to its accessibility and efficiency, along with the fact that it's more native to the Python way of development. This book will get you up and running with this cutting-edge deep learning library, effectively guiding you through implementing deep learning concepts.

In this second edition, you'll learn the fundamental aspects that power modern deep learning, and explore the new features of the PyTorch 1.x library. You'll understand how to solve real-world problems using CNNs, RNNs, and LSTMs, along with discovering state-of-the-art modern deep learning architectures, such as ResNet, DenseNet, and Inception. You'll then focus on applying neural networks to domains such as computer vision and NLP. Later chapters will demonstrate how to build, train, and scale a model with PyTorch and also cover complex neural networks such as GANs and autoencoders for producing text and images. In addition to this, you'll explore GPU computing and how it can be used to perform heavy computations. Finally, you'll learn how to work with deep learning-based architectures for transfer learning and reinforcement learning problems.

By the end of this book, you'll be able to confidently and easily implement deep learning applications in PyTorch.

Publication date:
November 2019


Section 1: Building Blocks of Deep Learning with PyTorch 1.x

In this section, you will be introduced to the concepts of deep learning and the various deep learning frameworks.

This section contains the following chapters:

  • Chapter 1Getting Started with Deep Learning Using PyTorch
  • Chapter 2Building Blocks of Neural Networks

About the Authors

  • Laura Mitchell

    Laura Mitchell graduated with a degree in mathematics from the University of Edinburgh and, since then, has gained over 12 years' experience in the tech and data science space. She is currently lead data scientist at Badoo, which is the largest online dating site in the world with over 400 million users worldwide. Laura has hands-on experience in the delivery of projects such as NLP, image classification, and recommender systems, from initial conception through to production. She has a passion for learning new technologies and keeping up to date with industry trends.

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  • Sri. Yogesh K.

    Sri. Yogesh K. is an experienced Data Scientist with a demonstrated history of working in the higher education industry and skilled in Python, Apache Spark, Deep Learning, Hadoop, and Machine Learning. He is a strong engineering professional with a Certificate of Engineering Excellence focused in Big Data Analytics and Optimization from International School of Engineering (INSOFE). Sri has trained 500+ working professionals in Data Science and Deep Learning from companies like Flipkart, Honeywell, GE, Rakuten, etc. Additionally, he has also worked on various projects that involved deep learning and PyTorch.

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  • Vishnu Subramanian

    Vishnu Subramanian has experience in leading, architecting, and implementing several big data analytical projects (artificial intelligence, machine learning, and deep learning). He specializes in machine learning, deep learning, distributed machine learning, and visualization. He has experience in retail, finance, and travel. He is good at understanding and coordinating between businesses, AI, and engineering teams.

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Latest Reviews

(1 reviews total)
A book that is not reviewed properly. Codes do not work, formatting is worst, and lots of spelling mistakes. Horrible experience

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