Subject

Data

The Random Cut Forest Algorithm

From Machine Learning for Business by Doug Hudgeon and Richard Nichol

In this article, you’ll see how SageMaker and the Random Cut Forest algorithm can be used to create a model that will highlight the invoice lines that Brett should query with the law firm. The result will be a repeatable process that Brett can apply to every invoice that will keep the lawyers working for his bank on their toes and will save the bank hundreds of thousands of dollars per year. Off we go!

Building Linear Models with Dask ML

From Data Science at Scale with Python and Dask by Jesse C. Daniel

This article delves into building linear models using Dask-ML.

Handling Data with R

From Practical Data Science with R, 2nd Ed. By Nina Zumel and John Mount

In this article, we demonstrate some ways to get to know your data, and discuss some of the potential issues that you’re looking for as you explore.

Ingesting Data from Files with Spark, Part 4

From Spark in Action, 2nd Ed. by Jean Georges Perrin

This is the last in a series of 4 articles on the topic of ingesting data from files with Spark. This section deals with ingesting a TXT file.

Slideshare: Finding Valuable Insights in Complex Data

From Graph Databases in Action by Dave Bechberger


slideshare-finding-valuable-insights-in-complex-data

How Does Computer Vision Work?

From Grokking Deep Learning for Computer Vision by Mohamed Elgendy

human_and_artificial_sensing
By Mohamed Elgendy

A Match Made in Heaven

From Deep Learning for Natural Language Processing By Stephan Raaijmakers

slideshare-a-match-made-in-heaven

 

The Guide to Computer Vision

From Grokking Deep Learning for Computer Vision By Mohamed Elgendy

slideshare-the-guide-to-computer-vision

Anticipating your Opponent with Minimax Search

From Deep Learning and the Game of Go by Max Pumperla and Kevin Ferguson

This article shows you how to use the minimax algorithm to help your game bot decide its next move.

Analyzing Stock Price Time Series with Fortran Arrays, Part 3

From Modern Fortran by Milan Curcic

In this part, we’ll conclude the article by using built-in functions and whole-array arithmetic to identify risky stocks, and find good times to buy and sell.

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