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The Automation Solution for the 10 (Not So Simple) Steps to Machine Learning

Thursday, May 03, 2018
1:00 PM. 45 minutes with Q&A

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As machine learning and artificial intelligence (AI) usher in the Fourth Industrial Revolution, everyone wants a piece. However, the machine learning process is complex and time-consuming, which discourages business analysts and executives from being involved.

Enter, automated machine learning — created to automate the machine learning process. Automating the steps within machine learning is a game changer that empowers business analysts and subject matter experts to uncover predictive insights and generate solutions to real-world problems without the need for programming or deep knowledge of algorithms.

You-ll Discover:

- The 10 steps in the machine learning lifecycle, and the reason AI projects take weeks or months to complete (hint: it's complex!)
- How automation improves each step of the current, manual machine learning process, delivering a reproducible process that is faster and with fewer errors
- Why automated machine learning enables data science for business analysts, executives, and SMEs
- A checklist of features to look for when choosing an automated machine learning solution for your organization


Colin Priest
Data Scientist & Director of Product Marketing, DataRobot

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