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

Prediction of the temperature in Berlin Tempelhof for the next couple of days. The model predicted 19.3° C for the first unknown day with the actual temperature being 19.8 °C.

Prediction of future global land temperature based on accuracy of different models and evaluating which model performs better

We predict GDP growth in R, comparing autoregressive models.

Autoregression on eye-gaze yields intent prediction.

Snippets and Utils for Machine and Deep Learning

Novelty Detection

Simple Moving Averages (SMA) and Autoregression (AR) Yule Walker Model for time series data representing temperature change and electrical consumption.

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.

Air Quality in Nairobi (Based on PM2.5 index)- A Time Series Analysis Projects - Building ARIMA ML Model. In this project, I work with data from one of Africa’s largest open data platforms openAfrica https://africaopendata.org/ .I’ll look at air quality data from Nairobi, Lagos, and Dar es Salaam; and build a time seriesmodel to predict PM 2.5 r…

COVID-19 Spread Prediction in Pakistan

R package that simulates and estimates the hystar model

Weather Data Analysis using Python, Pandas, SparkSQL, AutoRegression Model

Developed predictive models like ARIMA and logistic regression to analyze market trends and forecast movements. Employed statistical techniques like moving averages for trend insights and binary outcome predictions in financial analysis.

Time-series forecasting models

Autoregression is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step.

Transformer-based, character-level language model (GPT-like) to generate Shakespearean-like text given a seed string.