📌 Short Description: This repository presents a comparative analysis of ARIMA, LSTM & GRU models for time series forecasting using both quarterly sale and daily stock prices datasets. The project includes data preprocessing, model implementation, performance evaluation to identify the most effective forecasting techniques
Прогнозирование спроса на такси
Analyze trends and forecast daily revenues.
An ads and marketing based company helping businesses elicit maximum clicks @ minimum cost.
This model predicts co2 level in atmosphere on account of historical data.
Industrial Production Index Time Series Forecasting using a range of models including Holt-Winters, ARIMA, SARIMA, LSTMs, and Facebook's Prophet. The project focuses on predicting production trends through model evaluation, tuning, and visualization of forecasted outcomes.
Add a description, image, and links to the pacf-autocorrelation topic page so that developers can more easily learn about it.
To associate your repository with the pacf-autocorrelation topic, visit your repo's landing page and select "manage topics."