In this post, I’ll describe some of the core technologies and tools companies are beginning to evaluate and build. Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. The resource examples I’ll cite will be drawn from the upcoming Strata Data conference in San Francisco, where leading companies and speakers will share their learnings on the topics covered in this post.
AI and machine learning in the enterprise
When asked what holds back the adoption of machine learning and AI, survey respondents for our upcoming report, “Evolving Data Infrastructure,” cited “company culture” and “difficulties in identifying appropriate business use cases” among the leading reasons. Attendees of the Strata Business Summit will have the opportunity to explore these issues through training sessions, tutorials, briefings, and real-world case studies from practitioners and companies. Recent improvements in tools and technologies has meant that techniques like deep learning are now being used to solve common problems, including forecasting, text mining and language understanding, and personalization. We’ve assembled sessions from leading companies, many of which will share case studies of applications of machine learning methods, including multiple presentations involving deep learning:
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