Machine Learning in Practice

The best tools are born out of user necessity. AI Auditing was no different.

As the desire to scale machine learning programs grows, so does the frustration of the executives who attempt it.

Putting machine learning to practical business use is hard. Here’s hoping that these tips help make your journey a little easier.

Good managers are empathetic to their employees, and good machine learning managers understand the perspective of data scientists…

Machine learning is a technical process, but it starts and ends with people. The first step to structuring your machine learning project…

Grab a friend and try this quick experiment. Think of a simple song that almost everyone knows, like “Mary Had a Little Lamb.” Then using…

ethics: the discipline dealing with what is good and bad and with moral duty and obligation

You don’t just need project ideas. You need the means to carry them out. So let’s get to the final round: process questions.

This is the second in our three-part series laying out questions you should ask before you start a machine learning project.

Ask These Questions First

Think Task Automation, Not Job Automation

The “New Electricity” Needs A Lot of New Wiring

The author (left) with other young alumni of St. Lawrence University. Photo credit to St. Lawrence University’s Career Center.

Ranking The Most Published Researchers at NeurIPS/NIPS

Machine learning was recently applied to identify trends in smoking habits that could increase intervention and save the lives of smokers…

Michael Kaelin, RTI’s Chief Financial Officer, explained how the organization is beginning to explore machine learning.

Machine learning and/or deep learning have been at the peak since 2015, always marked as 2–5 years away from the Plateau of Productivity.

86% of data science decision makers across the Global 2000 believe machine learning impacts their industries today.