Tag: Machine Learning

Regularization

An introduction to the methods that help avoid over-fitting

Machine Learning Introduction

Necessary Machine Learning terminology explained

Webinar in Embedded AI, Machine Learning, and Analytics

“Many companies don’t know what steps to take to become digital, where to begin their journey to digital, or how to be sure they won’t waste money on innovation they can’t implement throughout their company to drive better business results…”

Machine Learning cheat sheet

You can follow the questions and get an overview of which algorithm to use

Get involved with the future of Artificial Intelligence

“When, if ever, will AI outperform humans at all intellectual tasks, and will it be a good thing?”

An interesting view of Andrew Ng

The guru of AI would like to pay displaced workers to learn new job skills, instead of an unconditional universal basic income

Connecting the different areas of the field

A nice map, showing how the various skills connect to each other

An overview of the most common ML types

Using different kinds of machine learning algorithms for different tasks

Myths and Facts About Super-Intelligent AI

“If you can’t explain it simply, you don’t understand it well enough”

A nice categorization of the most commonly used ML Algorithms

Split by categories, such as regression, decision tree and clustering

Type I and Type II error

In this case, a picture describes succinctly the difference

Free course in AI

I am definitely planning on taking it

Artificial Intelligence: Machine Learning Basics and its Applications

An article describing some of the basics around Machine Learning and Artificial Intelligence

Machine Learning Cheat Sheet

A consolidated overview of the most common approaches in ML