Subject

Data Science

More Sensitive Suggestions

From Deep Learning for Search by Tommaso Teofili

This article discusses how neural networks can help generate text that a human might write in order to provide more sensitive suggestions and enhance autocomplete functionality.

What Are GANs?

By Vladimir Bok, author of GANs in Action

This article discusses the history and meaning of Generative Adversarial Networks, and their potential.

What can Machine Learning do for your Business?


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From Machine Learning for Business by Doug Hudgeon, and Richard Nichol

Build a Full-Featured Data Solution


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From Fusion in Action by Guy Sperry

Privacy, Twitter, and Machine Learning: six questions with Andrew Trask

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.

PyTorch Crash Course, Part 3

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.

What do Cooking Pasta and Data Science Have in Common?

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.

PyTorch Crash Course, Part 2

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.

A Practice-Oriented Approach to Data Science


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From Practical Data Science with R, Second Edition
By Nina Zumel and John Mount

Get into Deep Learning


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From Grokking Deep Learning in Motion
By Beau Carnes

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