|
|
@@ -1,5 +1,49 @@
|
|
|
# Deep Learning with PyTorch
|
|
|
-Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann, published by Manning Publications.
|
|
|
|
|
|
-Manning: https://www.manning.com/books/deep-learning-with-pytorch
|
|
|
-Amazon: https://amzn.to/38Iwrff (affiliate link)
|
|
|
+This repository contains code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann, published by Manning Publications.
|
|
|
+
|
|
|
+
|
|
|
+
|
|
|
+The Manning site for the book is: https://www.manning.com/books/deep-learning-with-pytorch
|
|
|
+
|
|
|
+The book can also be purchased on Amazon: https://amzn.to/38Iwrff (affiliate link)
|
|
|
+
|
|
|
+## About Deep Learning with PyTorch
|
|
|
+
|
|
|
+This book has the aim of providing the foundations of deep learning with PyTorch and
|
|
|
+showing them in action in a real-life project. We strive to provide the key concepts underlying deep learning and show how PyTorch puts them in the hands of practitioners. In
|
|
|
+the book, we try to provide intuition that will support further exploration, and in doing
|
|
|
+so we selectively delve into details to show what is going on behind the curtain.
|
|
|
+Deep Learning with PyTorch doesn’t try to be a reference book; rather, it’s a conceptual companion that will allow you to independently explore more advanced material
|
|
|
+online. As such, we focus on a subset of the features offered by PyTorch. The most
|
|
|
+notable absence is recurrent neural networks, but the same is true for other parts of
|
|
|
+the PyTorch API.
|
|
|
+
|
|
|
+## Who should read this book
|
|
|
+
|
|
|
+This book is meant for developers who are or aim to become deep learning practitioners and who want to get acquainted with PyTorch. We imagine our typical reader
|
|
|
+to be a computer scientist, data scientist, or software engineer, or an undergraduateor-later student in a related program. Since we don’t assume prior knowledge of deep
|
|
|
+learning, some parts in the first half of the book may be a repetition of concepts that
|
|
|
+are already known to experienced practitioners. For those readers, we hope the exposition will provide a slightly different angle to known topics.
|
|
|
+ We expect readers to have basic knowledge of imperative and object-oriented programming. Since the book uses Python, you should be familiar with the syntax and
|
|
|
+operating environment. Knowing how to install Python packages and run scripts on
|
|
|
+your platform of choice is a prerequisite. Readers coming from C++, Java, JavaScript,
|
|
|
+Ruby, or other such languages should have an easy time picking it up but will need to
|
|
|
+do some catch-up outside this book. Similarly, being familiar with NumPy will be useful, if not strictly required. We also expect familiarity with some basic linear algebra,
|
|
|
+such as knowing what matrices and vectors are and what a dot product is.
|
|
|
+
|
|
|
+## About the authors
|
|
|
+
|
|
|
+Eli Stevens has spent the majority of his career working at startups in Silicon Valley,
|
|
|
+with roles ranging from software engineer (making enterprise networking appliances)
|
|
|
+to CTO (developing software for radiation oncology). At publication, he is working
|
|
|
+on machine learning in the self-driving-car industry.
|
|
|
+
|
|
|
+Luca Antiga worked as a researcher in biomedical engineering in the 2000s, and
|
|
|
+spent the last decade as a cofounder and CTO of an AI engineering company. He has
|
|
|
+contributed to several open source projects, including the PyTorch core. He recently
|
|
|
+cofounded a US-based startup focused on infrastructure for data-defined software.
|
|
|
+
|
|
|
+Thomas Viehmann is a machine learning and PyTorch specialty trainer and consultant based in Munich, Germany, and a PyTorch core developer. With a PhD in
|
|
|
+mathematics, he is not scared by theory, but he is thoroughly practical when applying
|
|
|
+it to computing challenges.
|
Eli Stevens