My solution to Kaggle challenge "IEEE Camera Model Identification" [top 3%]
Multiple Model Ensembling
TSML (Time Series Machine Learning Package) is package for Time Series data processing and prediction. It combines ML libraries from Python's ScikitLearn, R's Caret, and Julia using a common API and allows seamless ensembling and integration of heterogenous ML libraries to create complex models for robust time-series prediction.
Create an arbitrary graph of models and meta-models to form an ensemble. This can be viewed as a generalisation of stacking ensembles.
Stacking Classifier with parallel computing architecture based on Message Passing Interface.
Classify outcomes of dogs and cats in Austin animal shelter
Ensemble Stacking with RoBERTA & BiLSTM to estimate story point
This project enables rusty-blockparser user to manufacture the csv files into a ML dataset.
Some useful scripts for data processing and machine learning with python.
In this project I did exploratory data and geopolitical analysis to come up with a machine learning model which uses multilevel model stacking to predict the fare based on pickup points and drop off points.
Example of ensembled collection of "expert" learners fed into an encoder mlp for final action output
The Natixis Fraud Account Detection Workflow - Dataset Preparation & Algorithm
Assignments made for the Machine Learning Course held at Ain Shams University [2021-2022]
50.038 Computational Data Science Project - Spring 2026
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