Forecast for 3 methods of US emissions of CO2 to the atmosphere
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Updated
Jun 27, 2018 - MATLAB
Forecast for 3 methods of US emissions of CO2 to the atmosphere
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.
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.
Time-series forecasting models
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.
Delay Embedded Regressive Reduced Order Model
modeling autonomous guided vehicle using MATLAB Simulink. deterministic and stochastic system identification
Novelty Detection
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.
Simple Moving Averages (SMA) and Autoregression (AR) Yule Walker Model for time series data representing temperature change and electrical consumption.
Analyse underlying causalities of functional processes
Forecasting sales and economic demand for businesses with a time series approach using NeuralProphet
Snippets and Utils for Machine and Deep Learning
This is a final project for a Time Series course. My professor told me I could further work on it.
documenting my bachelor thesis
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