From Engineering Deep Learning Systems by Chi Wang and Donald Szeto
This article presents what prospective readers can expect to learn from this book and why you should learn it.
Read it if you’re a software developer interested in transitioning your skills to the field of deep learning system design or an engineering-minded data scientist who want to build more effective delivery pipelines.
In this video, machine learning expert Eli Stevens showcases how to use open-source libraries that are available in the PyTorch ecosystem to cut down the amount of the code that you want to write.
Deep dive with Carl Osipov into understanding automatic differentiation used by PyTorch autograd for deep learning
From Serverless Machine Learning in Action by Carl Osipov
From Math and Architectures of Deep Learning by Krishnendu Chaudhury
By Robert Munro, author of Human-in-the-Loop Machine Learning
From Pandas in Action by Boris Paskhaver
From Deep Learning with PyTorch by Eli Stevens and Luca Antiga
This article explores the use and capabilities of GANs, using a fictional (and inadvasible) example of aspiring art forgers.
From Deep Learning with PyTorch
by Eli Stevens and Luca Antiga
In this article, we explore some of PyTorch’s capabilities by playing generative adversarial networks.