Slideshare: Getting up and running with Spark


By Jason Kolter

Slideshare: Build Your Own Go

From Playing Machine With Deep Learning and the Game of Go


By Max Pumperla and Kevin Ferguson

Slideshare: Deep Learning for R Users


By François Chollet with J. J. Allaire

Managing Quality

By Tryggvi Björgvinsson

This article discusses quality management in terms of data and data projects. When you know what your users need or want, you’ll have to manage those expectations somehow, but how do you manage quality? It turns out that you approach it similarly to how you would try to properly answer a question.

Slideshare: Improving Search Performance


By Tommaso Teofili

Learning From the Past: data usability

By Tryggvi Björgvinsson

Everywhere we go we are surrounded by data, but it’s not always simple to interpret. Not only that, it’s also rather easy to mistakenly interpret data. This article, adapted from chapter 1, introduces the idea of “data usability” and goes into why it’s important in today’s data-rich world.

Slideshare: Murder Mystery: a data project


By Tryggvi Björgvinsson

Deep Learning for Text  

By François Chollet

In this article, we’ll learn about deep learning models that can process text (understood as sequences of word or sequences of characters), timeseries, and sequence data in general.

Solving Mazes with Swift

By David Kopec

This article is all about finding a path through mazes, which is an analogous to many common search problems in computer science. Examples are in Swift.

How Streams Relate to Database Tables in Kafka

By Bill Bejeck

In this article, we’re going to look deeper into adding state. Along the way, we’ll get introduced to new abstraction, the Ktable, after which we will move further on to discuss how event streams and database tables relate to one another in ApacheKafka (Kstream and Ktable, respectively).

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