Subject

Data

Constructing a Yelling App with Kafka Streams

By Bill Bejeck

This article will quickly get you off the ground and show you how Kafka Streams works. We’re going to make a toy application that takes incoming messages and upper-cases the text of those messages, effectively yelling at anyone who reads the message. This application is called the “Yelling Application”.

Slideshare: Specifying Data Type in R

From Data Munging with R

slideshare-specifying-data-type-in-r

By Dr. Jonathan Carroll

Slideshare: A* Search in Swift: navigating a maze

From Classic Computer Science Problems in Swift

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By David Kopec

Introducing Keras: deep learning with Python

By François Chollet

This article introduces Keras, a deep learning library for Python that can be used with Theano and TensorFlow to build almost any sort of deep learning model.

Building Your Vocabulary

In this article, you will learn about tokenization in Natural Language Processing.

Save 37% off Natural Language Processing in Action with code fcclane at manning.com.

Slideshare: How can I improve data flow downstream?


slideshare-how-can-i-improve-data-flow-downstream

Save 42% with code kafkastreams. How can I improve data flow downstream?

Slideshare: Analyzing meaning using the “Bag of Words” vector


slideshare-analyzing-meaning-using-the-bag-of-words-vector

By Hobson Lane, Cole Howard, and Hannes Max Hapke

Analyzing meaning using the “Bag of Words” vector. Save 42% off Natural Language Processing in Action with code sllane at manning.com

How to Choose Statistical Software Tools: the good, the bad, and the helpful for data science projects

By Brian Godsey

In this article, you will learn about how to choose statistical software tools – what’s important to look for and the things you should consider while choosing the software that’s right for the job.

Save 37% off Think Like a Data Scientist with code fccgodsey.

Check Your Assumptions about Your Data!

By Brian Godsey

In this article, we’re going to discuss the importance of identifying and reviewing any assumptions you might have about the data you’re working with.

Slideshare: How can I get started with Deep learning?


slideshare-how-can-i-get-started-with-deep-learning

Save 42% with code deeplearning

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