From Python for Big Datasets by John T. Wolohan
From Spark in Action, Second Edition by Jean George Perrin
From Graph-Powered Machine Learning by Alessandro Negro
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 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
