BCE v0.4 - Practical implementation of Compression via Substring Enumeration
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Updated
Jul 4, 2017 - C++
BCE v0.4 - Practical implementation of Compression via Substring Enumeration
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.
Ved Stationary Ecommerce WebApp
MATLAB code for deseasonalizing hourly PV/GHI data using a ridge-regularized ELM. It extracts a phase-based seasonal component, computes stationary residuals (PACFsum), and performs a grid search on lag length and hidden units. Includes plots and tools for tuning ELM parameters in solar forecasting.
This project utilizes time series forecasting models, such as VAR and ARIMAX, to predict the bike share demand in Seoul. In turn, ensuring availability and minimizing waiting times for customers.
My bachelor's and master's theses
Análisis y notebooks de 'Forecasting Sticker Sales'. Incluye EDA, tratamiento de NaNs y modelado para la predicción estacionaria de demanda de stickers utilizando forecast y arima.
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