Consulting Data Science Machine Learning Predictive Modeling 
CIO Business Intelligence
JULY 28, 2022
They’ve also created a relationship with universities, setting up a pipeline of emerging technology-focused interns, who work at the company, gain experience in data science, and then can potentially be hired after they graduate. . Expanding data science teams. These people are making up a data science support system.
IBM Big Data Hub
OCTOBER 16, 2023
Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029. Many stock market transactions use ML.
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DataRobot
NOVEMBER 1, 2021
Practitioners in the AI space are focused on the speed and accuracy of model predictions. But the end game for the applicability of models is not in the predictions, but the decisions they enable, and predictive models alone don’t ensure better decisions. What Is Decision Intelligence?
Smarten
MAY 31, 2022
The technology research firm, Gartner has predicted that, ‘predictive and prescriptive analytics will attract 40% of net new enterprise investment in the overall business intelligence and analytics market.’ Access to Flexible, Intuitive Predictive Modeling. Forecasting. Classification. Hypothesis Testing. Correlation.
Smarten
FEBRUARY 17, 2022
Without understanding the shift in workflow, responsibilities and how the use of data will change the enterprise, it is unlikely that the business will succeed in its Citizen Data Scientist initiative.
DataRobot Blog
NOVEMBER 9, 2017
You should hire expensive consultants and PhD’s instead.” I work for a software company that has built an automated machine learning platform. I’ve spent the last 2+ years working with business analysts and MBA’s to build predictive models. What matters is making progress. You’ve got to start somewhere.
O'Reilly on Data
MARCH 20, 2019
Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.
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