A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
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Updated
Sep 25, 2024 - Python
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
Time series forecasting with machine learning models
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
CryptoCurrency prediction using machine learning and deep learning
Time-series analysis of the electricity load consumption in the Mumbai Metropolitan Region.
Detects PM2.5 levels based on daily atmospheric conditions
Customers knowledge, supply chain movement and sales forecasting, Customer Lifetime value, churn and survival analysis
Estimate S-ARIMA-X models with Stochastic Gradient Descent or Kalman Filter
TS forecasting with time weighted mean method
Complete solution for MOFC M5 Forecasting in kaggle.
Real time streaming of a time series with corresponding forecasts.
Backtesting software for intraday and daily timeframe SARIMAX forecasting model. Capable of forecasting on any asset class with backtesting capability across various parameter sets customizable by the user.
SARIMAX model for forecast traffic volume
Returns best ARIMA model according to information criteria. Search over possible model within the order constraints provided.
Automated the process of training time-series data with multiple Machine Learning and Stats Models to output the most accurate forecast result
Forecasting the growth of GitHub repositories (in Python and R languages) over the next 5 years.
Sarima using flask framework for building a rest API model
Autoregression model for predicting results on metrics and Cohort analysis.
Multivariate Forecasting of Hourly Electricity Consumption with ARIMAX, SARIMAX, and LSTM
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