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Ensemble models on synthetic data

Kats : a toolKit to Analyze Time Series

![](kats_logo_small.png)

Kats, a toolKit to analyze time series data, a light-weight, easy-to-use, and generalizable framework to perform Time Series analysis. Time Series analysis is an essential component of Data Science and Engineering work at Facebook, from understanding the key statistics and characteristics, detecting regressions and anomalies, to forecasting future trends. There are a few internal and external packages that can perform certain analyses, while a unified in-house framework is desired. Kats aims to provide the one-stop shop for time series analysis, like detection, forecasting, feature extraction, multivariate analysis, etc.

Our goal is to provide time series algorithms and models for Facebook's Infrastructure, Facebook's family products, internal library users, and open source communities in the near future, our vision on Kats ecosystem is showing in following figure.

References

  • Kats v0.1 Release
  • Kats H1 2020 Plan

Past Presentations

  • Kats IDS Big Bet Pitch
  • Introduction to Kats
  • Kats IDS Big Bet Review - 02/25/2020
  • Kats IDS Big Bet Review - 04/02/2020

Tutorials

We use the kats kernel in bento for all the following tutorials.

  • Kats Tutorial
  • Kats Grid Search Demo
  • Decomposition and Outlier Detection
  • Ensemble Models

The Team

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{{ WS/Styles#card-people-stylized| 100012665821683 | title=Research Data Scientist }}

Tasks

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