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!
From Data Science at Scale with Python and Dask by Jesse C. Daniel
This article delves into building linear models using Dask-ML.
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.
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.
From Graph Databases in Action by Dave Bechberger
From Grokking Deep Learning for Computer Vision by Mohamed Elgendy
By Mohamed Elgendy
From Grokking Deep Learning for Computer Vision By Mohamed Elgendy
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.
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.
