Informer is a new transformer model for long sequence time series forecasting that won best paper at the AAAI conference.

Introduction

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How to leverage Flow-Forecast, Docker, Terraform, Airflow, Kubernetes and ONNX to easily scale your deep time series models to production workloads.

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Version 0.95 of Flow Forecast includes complete support for probabilistic models, multitask forecasting, bug fixes and much more

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New Features/Bug Fixes

  • Complete support for multitask learning: Flow forecast now allows users to easily forecast multiple targets at once. For an easy to use tutorial see this notebook.
  • Log and sort on multiple metrics: Flow Forecast now allows you to…


Lessons and tips learned from training hundreds of PyTorch time series forecasting models in many different domains

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Frame your problem

  • Anomaly detection: This is a general technique to detect outliers in…


A deep dive into the latest literature in time series forecasting and how you can use them for your business use cases

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Transfer learning’s latest frontier

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Lessons learned from building an open-source deep learning for time series framework.

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Background


More and more data science teams seem to be hopping on the scrum bandwagon, but is it a good idea?

Scrum is not suitable for most data science teams. Image source


Accurate multivariate time series forecasting and classification remains a central challenge for many businesses and non-profits.


Utilizing the latest advances in machine learning for COVID-19 forecasting

A image of one of our model’s projections for the Bronx county in NYC starting May 9th. Actual cases are shown in the orange and our model’s projections are shown in blue. You can see our model accurately forecasts the general downward trajectory, however still does not capture all the daily noise.

Isaac Godfried

Deep learning researcher. Creator/Maintainer of @FlowTemporal

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