Gartner Blog Network

Tag: 'machine-learning' Blog Posts

from the Gartner Blog Network

Machine Learning - Shift from Modeling to Engineering

by Sumit Agarwal  |  August 21, 2020

In 2012, Harvard Business Review had published Data Scientist as the sexiest job of 21st century. In 2019, an Indeed survey had Computer Vision Engineer and Machine Learning Engineer as...

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Robust Machine Learning needs Data and a Lot More

by Sumit Agarwal  |  May 27, 2020

“It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.” Sir Arthur Conan Doyle,...

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Re-establish Organizational Trust in Predictive Models

by Joseph Enever  |  April 15, 2020

Photo by Franki Chamaki on Unsplash Coronavirus upended marketing’s predictive models. Beyond that, there’s an additional issue: how do you manage to rebuild your colleagues’ trust in them?  Because a...

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Unprecedented times + machine learning = poor experiences?

by Jason McNellis  |  April 3, 2020

As marketers move from reacting to COVID to planning for a new-normal, it’s time to re-evaluate machine learning capabilities. Obviously digital engagement and retail consumption patterns have shifted in most...

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When Machine Learning Prediction Excels

by Jitendra Subramanyam  |  July 6, 2019

Meet the Chief Data and Analytics Officer research team | Check out our research In the previous post, Prediction Models: Traditional versus Machine Learning, we looked at 3 kinds of...

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Prediction Models: Traditional versus Machine Learning

by Jitendra Subramanyam  |  June 8, 2019

Meet the Chief Data and Analytics Officer research team | Check out our research Machine learning models are constructed differently from traditional quantitative models. Two Types of Traditional Prediction Models...

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Training versus Inference

by Paul DeBeasi  |  February 14, 2019

Few data-driven technologies provide greater opportunity to derive value from Internet of Things (IoT) initiatives as machine learning. The accelerated growth of data captured from the sensors in IoT solutions...

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Machine Learning Integration Options

by Paul DeBeasi  |  January 30, 2019

Machine learning projects are inherently different from traditional IT projects in that they are significantly more heuristic and experimental, requiring skills spanning multiple domains, including statistical analysis, data analysis and...

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Architect Machine Learning with IoT

by Paul DeBeasi  |  January 25, 2019

Developers with no data science experience are now able to integrate Machine Learning (ML) with IoT. As the number of IoT endpoints proliferate, the need for organizations to understand how...

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More on “AI for cybersecurity”

by Augusto Barros  |  January 4, 2019

There is a very important point to understand about the vendors using ML for threat detection. Usually ML is used to identify known behavior, but with variable parameters. What does...

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