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Time Series Forecasting and Anomaly detection in Python

This repository explores various techniques for analysis, forecasting, and anomaly detection. It features end-to-end deployment using Fast API and Streamlit and ML Systems design This repository explores a diverse set of techniques for time series analysis forecasting. Notably, it features end-to-end deployment utilizing Fast API and Streamlit, along with ML systems design

Featured modles

  • ARMA
  • ARIMA
  • Auto ARIMA
  • Facebook Prophet
  • KNN
  • XGBoost
  • Random Forest
  • LSTM

Data Source

UC Irvine Machine Learning Repository and Kaggle

Data Repo

License

This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Citation

Advanced Forecasting with Python by Joos Korstanje (Apress, 2021)

Darts: User-Friendly Modern Machine Learning for Time Series

Machine Learning Engineering with Python Textbook "by Andrew McMahon

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Time Series Forecasting using ARMA, ARIMA, AutoArima , Facebook Prophet, KNN, RandomForest XGBoost and LSTM

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