Remove 2001 Remove 2011 Remove Interactive Remove Machine Learning
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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

The company has been on a continuous journey to adapt its internal and external processes to new business needs and opportunities since 2001.” Following this, in 2002, it began delivering its knowledge to customers in online format, using dashboards and interactive reports that provided easier and faster access to data and analysis.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. That presented an opportunity to learn, putting me in the same position as much of the audience. Fun fact: in 2011 Google bought remnants of what had previously been Motorola.

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Themes and Conferences per Pacoid, Episode 5

Domino Data Lab

Meanwhile, employers who are betting that their teams accomplish substantial projects in data science, machine learning, data engineering, artificial intelligence, etc., In terms of teaching and learning data science, Project Jupyter is probably the biggest news over the past decade – even though Jupyter’s origins go back to 2001!

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Data Science at The New York Times

Domino Data Lab

Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way. I still believe that data science is the craft of trying to apply machine learning to some real world problem.