Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Chenhui Hu

Chenhui Hu
Data Scientist, Microsoft

Website

Chenhui Hu is a data scientist in the Cloud and AI Division at Microsoft. He works on developing machine learning and big data solutions for internal and external customers. His current interests include time series forecasting, natural language processing, large-scale machine learning, and deep learning. He received his PhD degree from Harvard University with a focus on imaging data mining and signal processing. He has presented his work in many international conferences including O’Reilly AI Conference 2019 and O’Reilly Strata 2019.

Sessions

2:40pm–3:20pm Wednesday, March 27, 2019
Dilated neural networks for time series forecasting
Data Science, Machine Learning & AI
 Location: 2016
Secondary topics:  Deep Learning, Temporal data and time-series analytics
Chenhui Hu (Microsoft)
Average rating: ****.
(4.67, 6 ratings)
Dilated neural networks are a class of recently developed neural networks that achieve promising results in time series forecasting. Chenhui Hu discusses representative network architectures of dilated neural networks and demonstrates their advantages in terms of training efficiency and forecast accuracy by applying them to solve sales forecasting and financial time series forecasting problems. Read more.