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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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6 Spectacular Reasons You Must Master the Data Sciences in 2020

Smart Data Collective

The global demand for big data is surging. It is understandable that many computer science majors are considering pursuing careers in this evolving field. Is the Booming Big Data Field Right for You? Everyone has heard about Data Science in 2020. One of them is Data Science.

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Data Science, Past & Future

Domino Data Lab

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

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Email Marketers Use Data Analytics for Optimal Customer Segmentation

Smart Data Collective

Since its inception in 2001, Mailchimp has had more than two decades of expertise in email marketing for millions of subscribers. Data science. Data science plays a vital role in the efficacy, quality, and other aspects of email marketing campaigns and their administration.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Rinse, lather, repeat. Those are table stakes in this game.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.