Tag

Machine Learning

Serverless AI Solutions

From AI as a Service by Peter Elger, Eoin Shanaghy, and Johannes Ahlmann

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Machine Learning from the Ground up

From Machine Learning for Mortals (Mere and Otherwise) by Hefin I. Rhys

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The Magic of Graphs and Machine Learning

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From Graph-Powered Machine Learning by Alessandro Negro

Interview: Taking Advice from a Machine

Six Questions for Kim Falk author of Practical Recommender Systems

By Frances Lefkowitz

Kim Falk is a Copenhagen-based data scientist who works with machine learning and recommender systems. Keep up with him @kimfalk on Twitter.

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.

How Does Computer Vision Work?

From Grokking Deep Learning for Computer Vision by Mohamed Elgendy

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By Mohamed Elgendy

A Match Made in Heaven

From Deep Learning for Natural Language Processing By Stephan Raaijmakers

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The Guide to Computer Vision

From Grokking Deep Learning for Computer Vision By Mohamed Elgendy

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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.

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