What’s Next for Machine Learning in Time Series

Ira Cohen on Challenges and Opportunities in Time Series.

SubscribeApple • Spotify • Stitcher • Google • AntennaPod • Podcast Addict • RSS.

Ira Cohen is co-founder, Chief Data Scientist at Anodot1, a startup that uses time series tools to monitor  business data in real time, so organizations can proactively resolve revenue, cost, and customer experience issues before they impact business performance. We recently wrote a well-received post that provided a detailed overview on the state of technologies for collecting, storing, and unlocking time series. In this episode we discuss the many existing challenges faced by teams who deal with time series.  These challenges provide excellent opportunities for aspiring entrepreneurs and builders, which is why we wanted to highlight them.

Subscribe to the Gradient Flow Newsletter

Highlights in the video version:

Image: from “Trends and Opportunities in Time Series”.

Related content:

If you enjoyed this episode, please support our work by encouraging your friends and colleagues to subscribe to our newsletter:

[1] Ben Lorica is an advisor to Anodot and other startups.

[Image: Transitions by Ben Lorica, using images from Infogram.]