A python multi-variate time series prediction library working with sklearn

I perform time series analysis of data from scratch. I also implement The Autoregressive (AR) Model, The Moving Average (MA) Model, The Autoregressive Moving Average (ARMA) Model, The Autoregressive Integrated Moving Average (ARIMA) Model, The ARCH Model, The GARCH model, Auto ARIMA, forecasting and exploring a business case.

Time Series Analysis Concepts Explained with examples

This is the official implementation of the paper "Generating Emotive Gaits for Virtual Agents Using Affect-Based Autoregression".

Time-series forecasting models

Matlab Machine Learning application for predicting Arsenal F.C. football results during 2013-2014 season using self-programmed multi-class (1-against-rest approach) Naive Bayes and an implementation of AutoRegression.

documenting my bachelor thesis

ARIMA model from scratch using numpy and pandas.

COVID-19 Spread Prediction in Pakistan

Forecast for 3 methods of US emissions of CO2 to the atmosphere

🏅 2019 한국통계학회 춘계학술논문대회 프로젝트

R Shiny application for measuring the effect of foods on gastrointestinal symptoms. Public on shinyapps.io

Novelty Detection

Implement gradient descent in linear regression problems, construct and evaluate simple linear models, and use feature engineering to create more complex supervised machine learning models.