Challenges of Deep Learning for Time Series Data
Published:Jun 21, 2020 10:24
•1 min read
•Hacker News
Analysis
The article from Hacker News highlights the inherent difficulties in applying deep learning techniques to time series data, characterized by issues such as data corruption and irregularity. This discussion provides valuable context on the practical hurdles researchers and practitioners face when working with real-world time series.
Key Takeaways
Reference
“The article's context emphasizes the issues of 'corrupt, sparse, irregular and ugly' time series data.”