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6 trends framing the state of AI and ML

O'Reilly on Data

Our analysis of ML- and AI-related data from the O’Reilly online learning platform indicates: Unsupervised learning surged in 2019, with usage up by 172%. Deep learning cooled slightly in 2019, slipping 10% relative to 2018, but deep learning still accounted for 22% of all AI/ML usage. Growth in ML and AI is unabated.

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AI adoption in the enterprise 2020

O'Reilly on Data

The new survey, which ran for a few weeks in December 2019, generated an enthusiastic 1,388 responses. This year, about 15% of respondent organizations are not doing anything with AI, down ~20% from our 2019 survey. It seems as if the experimental AI projects of 2019 have borne fruit. But what kind?

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Topics to watch at the Strata Data Conference in New York 2019

O'Reilly on Data

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. 221) to 2019 (No. 40; it peaked at Strata NY 2018 at No. 30 in 2018.

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What you need to know about product management for AI

O'Reilly on Data

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. Spring 2019 Full Stack Deep Learning Bootcamp (Berkeley).

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Driving Discovery and Experimentation in your Organization

Speaker: Teresa Torres, Product Discovery Coach, Product Talk, David Bland, Founder and CEO, Precoil, and Hope Gurion, Product Coach and Advisor, Fearless Product LLC

This is where continuous discovery and experimentation come in. Join Teresa Torres (Product Discovery Coach, Product Talk), David Bland (Founder, Precoil), and Hope Gurion (Product Coach and Advisor, Fearless Product) in a panel discussion as they cover how - and why - to build a culture of discovery and experimentation in your organization.

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How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4

KDnuggets

In this fourth and final part of the ultralearning data science series, it's time to take the final steps toward developing a deep understanding of the fundamentals and learning how to experiment -- the two aspects that are the ultimate keys to ultralearning.

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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

It is also important to have a strong test and learn culture to encourage rapid experimentation. What are you most looking forward to about CDAOI Insurance 2019? A properly set framework will ensure quality, timeliness, scalability, consistency, and industrialization in measuring and driving the return on investment.

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