From Spark with Java by Jean Georges Perrin
You’ve probably seen a simple use-case where Spark ingests data from a CSV file, then performs a simple operation, and then stores the result in the database. In this article, you’re going to see what happened behind the scenes.
Privacy, Twitter, and Machine Learning
Andrew Trask, author of Grokking Deep Learning
By Frances Lefkowitz, Manning Development Editor
Andrew Trask is a researcher pursuing a Doctorate at Oxford University, where he focuses on Deep Learning with an emphasis on human language. He is also a leader at OpenMined.org, an open-source community of researchers and developers working on creating free and accessible tools for secure AI. Previously, Andrew was analytics product manager at Digital Reasoning, where he trained the world’s largest artificial neural network (with over 160 billion parameters) and helped guide the analytics for the Synthesys cognitive computing platform, which tackles problems in government intelligence, finance, and healthcare. Grokking Deep Learning is his first book.
Find Andrew online at his blog (iamtrask.github.io) and @iamtrask on Twitter.
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.
From Data Science at Scale with Python and Dask by Jesse C. Daniel
This article discusses Dask, how it compares to Apache Spark, and how to create and understand directed acyclic graphs using the example of the delicious Italian pasta dish bucatini all’Amatriciana.
From Deep Learning with PyTorch by Eli Stevens and Luca Antiga
In this article, we explore some of PyTorch’s capabilities by playing with pre-trained networks.
From Practical Data Science with R, Second Edition
By Nina Zumel and John Mount
From Grokking Deep Learning in Motion
By Beau Carnes
From Reinforcement Learning in Motion
By Phil Tabor
From GANs in Action
By Jakub Langr and Vladimir Bok
From Deep Learning with PyTorch by Eli Stevens and Luca Antiga
This article introduces you to PyTorch and discusses why you might want to use it in your deep learning projects.