The repository provides an in-depth analysis and forecast of a time series dataset as an example and summarizes the mathematical concepts required to have a deeper understanding of Holt-Winter's model. It also contains the implementation and analysis to time series anomaly detection using brutlag algorithm.

Time-series analysis of the electricity load consumption in the Mumbai Metropolitan Region.

Identified the most appropriate Time-Series method to forecast drought in African countries, acting as a critical early warning for drought managements

This repository is aiming to Time Series Forecast over a given dataset. The goal of the exercise is to find the most appropriate model and make some predictions.

Time series forecasting using ML forecasting models

Forecasting Wine Sales of Two Different types of Wine. After thorough Data Analysis, different models have been used and tested such as Exponential Smoothing Models, Regression, Naive Forecast, Simple Average, Moving Average. Stationarity of the data is checked. Automated Version of ARIMA/SARIMA Model built. Comparison of Models.

Financial modeling in Python - ARIMA, GARCH, Black-Scholes, CAPM, XGBoost

Building Time Series Exponential Smoothing models to forecast temperature and ARIMA model to forecast weekly sales for a retail store.

Time Series Analysis Projects