A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
CryptoCurrency prediction using machine learning and deep learning
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
Detects PM2.5 levels based on daily atmospheric conditions
Time-series analysis of the electricity load consumption in the Mumbai Metropolitan Region.
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
Complete solution for MOFC M5 Forecasting in kaggle.
Real time streaming of a time series with corresponding forecasts.
Automated the process of training time-series data with multiple Machine Learning and Stats Models to output the most accurate forecast result
SARIMAX model for forecast traffic volume
Explore NVIDIA's stock dynamics with this project, using a mix of traditional and deep learning models to forecast stock prices and analyze the influence of market sentiment. Integrates ARIMA, LSTM, and more to provide deep insights.
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.
Returns best ARIMA model according to information criteria. Search over possible model within the order constraints provided.
Predict the future of your network using the best time series ML model that fit with your traffic.
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.
Forecasting daily electricity consumption 💡 with Portuguese weather data on precipitation 🌧️ and temperature 🌡️
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