Use auto encoder feature extraction to facilitate classification model prediction accuracy using gradient boosting models

Model that uses 10 different algorithms to predict the revenue of a movie before it's release

multi-variate deep time series forecasting ensemble models

An NHL expected goals (xG) model built with light gradient boosting.

Evaluation and Implementation of various Machine Learning models for creating a "Banking/Financial Transaction Fraud Prevention System"

Project work related to various hackathons

Comparison of ensemble learning methods on diabetes disease classification with various datasets

A binary classification task performed with machine learning in Python. The dataset's target distribution is heavily imbalanced. The model performance was evaluated with F1 scores.

How to do a simple end-to-end machine learning classification project using the telco churn dataset

A model build on RAVDESS dataset, for speech emotion recognition. 85.59% validation accuracy

This repository contains the project where the goal is to develop a machine learning model that can accurately predict car prices based on various features. We explored multiple models including K-Nearest Neighbor, Decision Tree, Catboost Classifier, and Light Gradient Boosting Classifier.