Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Video – Alexa On The Edge – A Case Study in Customer-Obsessed Research from Susanj of Amazon
 Event: Machine Learning Week 2021 Keynote: Alexa On The Edge...
Why AI Isn’t Going to Replace Data Scientists Any Time Soon
 Should data scientists consider AI a threat to their...
“Doing AI” Is a Mistake that Detracts from Real Problem-Solving
  A note from Executive Editor Eric Siegel: Richard...
Getting the Green Light for a Machine Learning Project
  This article is based on the transcript of...

data science

The Three Reasons Companies Seek University Partnerships

 In addition to this article, Dr. Priestley will also present on this topic at Predictive Analytics World for Business in Las Vegas, May 31-June 4, 2020. For details about her session, “How Leading Enterprises Leverage Universities to Boost Analytical Innovation and Tap Talent”, click here.   This is part 2 of a 5-part series on

Keeping Data Inclusivity Without Diluting your Results

 Originally published in WeAllCount.com, January 17, 2020 Let’s say you are surveying 100 people out of 10,000. You want to analyze the data from your sample of 100 to get answers about the likely behaviors and preferences...

The ML Times Is Growing – A Letter from the New Editor in Chief

  Dear Reader, As of the beginning of January 2020, it’s my great pleasure to join The Machine Learning Times as editor in chief! I’ve taken over the main editorial duties from Eric Siegel, who founded the...

The 4 Hottest Trends in Data Science for 2020

 Originally published in Towards Data Science, January 8, 2020 2019 was a big year for all of Data Science. Companies all over the world across a wide variety of industries have been going through what people are...

How to Perfect Your Data Science Resume in 3 Easy Steps

 Breaking into the world of Data Science can be tricky, but writing a killer resume gives you a better chance of landing a job in this highly competitive field. There are a few simple steps you can...

Three Common Mistakes That Can Derail Your Team’s Predictive Analytics Efforts

  Originally published by Harvard Business Review With today’s high demand for data scientists and the high salaries that they command, it’s often not practical for companies to keep them on staff.  Instead, many organizations work to...

Why Your Analytics Must Ask the Data “Good” Questions — Ones that Reduce Data

 The problem of monetizing Big Data, or improving its usefulness in decision-making, stands out in every forward-looking organization today. To solve it, as everyone knows by now, it is not enough to store or manage it. We...

The Art of Data Science

 With much of the latest discussion focused on the latest techniques in machine learning  and in particular deep learning, the significant benefits of machine learning and deep learning are now a public reality. Yet, machine learning in...

Mind Your Own Text: Public Data for Political Insights

 Who is your favorite president? Can Data Science aid in evaluating presidents and their policies? From the suburbs of Washington, D.C., our research group at George Mason University (Abhishek Kamath, Suyameendra Wadki, and Abhishek Madhusudhan) have developed...

Machine Learning Tip: Nested Cross Validation – When (Simple) Cross Validation Isn’t Enough

 Several scientific disciplines have been rocked by a crisis of reproducibility in recent years . Not long ago, Bayer researchers found that they were only able to replicate 25% of the important pharmaceutical papers they examined , and an...

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