End-to-End Deep Learning for Time Series Forecasting and Analysis


Deep learning has made major strides in computer vision and NLP. Transformers and LLMs now dominate most NLP applications both in industry and academia. Although not quite with the volume or hype of NLP a large variety of academic research has also shown the utility of deep learning models such as the transformer or LSTMs for time series forecasting and classification.

However, many companies still prefer to use simple methods like Linear Regression or ARIMA. Moreover, training and generalizing deep time series models to forecest/classify real world business data still has a high learning curve and on the surface is out of reach to many businesses. In this talk I will dive into several open source deep learning for time series frameworks (Flow Forecast, PyTorch Geometric Temporal, HuggingFace, etc) that aim to ease the process of model selection, fine-tuning, feature selection and evaluation. We will walk through a real world time series forecasting problem step-by-step with data collection, pre-processing, model training, hyper-parameter tuning, validation, and deployment. We will also discuss the tradeoffs of deep learning over traditional methods for time series forecasting and analysis. Finally, we will touch upon some open areas of ground breaking research such as multi-modal time series forecasting and generalized pre-training of time series models (similar to in NLP), and utilizing neural ordinary differential equations.

Participants will leave with a solid understanding of how to get started utilizing OSS frameworks to forecast and analyze their time series data. They will also gain knowledge of what areas of research to monitor in the time series space and how these techniques will be applicable to their datasets.


Isaac Godfried is a data scientist at SimSpace. Isaac specializes in utilizing deep learning on real world problems in cybersecurity, climate, healthcare, and agriculture. He is the author and principal maintainer of Flow Forecast a deep learning for time series framework in PyTorch.

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