Ray Summit 2020 has ended
View More Details for Ray Summit & Registration Information.
Please note: All Sessions are in Pacific Daylight Time (PDT), UTC-7

Thursday, October 1 • 11:10am - 11:40am
Project Zouwu: Scalable AutoML for Telco Time Series Analysis using Ray and Analytics Zoo - Ding Ding, Intel

Sign up or log in to save this to your schedule, view media, leave feedback and see who's attending!

Feedback form is now closed.

Time series analysis plays a crucial rule in the telecom applications, such as network quality analysis, network capacity forecast, smart power management, etc. There’s a recent trend to apply machine learning methods (especially neural networks) to such problems, and they are reported to perform better in many cases than traditional methods such as autoregression and exponential smoothing.

However, building the machine learning applications for time series forecasting can be a laborious and knowledge-intensive process. In this talk, we present Project Zouwu, which provides Automated Machine Learning (AutoML) to time series analysis for Telco application. It is built on top of Ray (https://github.com/ray-project/ray) and Analytics Zoo (https://github.com/intel-analytics/analytics-zoo), so as to automate the process of feature generation and selection, model selection and hyper-parameter tuning in a distributed fashion. We will also share some real-world experience and “war stories” of earlier users.

avatar for Ding Ding

Ding Ding

Machine Learning Engineer, Intel
Ding Ding is a machine learning engineer in Intel’s ML solution platform team, where she works on developing distributed machine learning and deep learning algorithms. She is an active contributor to the BigDL and Analytics Zoo projects.

Thursday October 1, 2020 11:10am - 11:40am PDT
Virtual 3
  Case Studies
  • Slides Included Yes