A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

Some of the topics, algorithms and projects in Machine Learning & Deep Learning that I have worked on and become familiar with.

Diabetes is a medical disorder that affects how the body uses food for energy. When blood sugar levels rise, the pancreas releases insulin. If diabetes is not managed, blood sugar levels can rise, increasing the risk of heart attack and stroke. We used Python machine learning to forecast diabetes.

This repository contains functions/codes related to different methods of machine learning for classification and clustering in python.

Coursework on Introduction to Machine Learning - CS M146

A collection of boosting algorithms written in Rust 🦀

This repository contains a comprehensive guide and implementation of ensemble modeling techniques, specifically focusing on Boosting, Bagging, and Voting. Ensemble methods are powerful techniques in machine learning that combine the predictions from multiple models to improve overall performance and robustness.

AIML Projects

Implemented Machine Learning Models to predict Stroke

Machine Learning project - CMP2024 - Computer Engineering - Cairo University

To build a classification system to predict whether a customer will churn or not based on the IBM Telecom Data from Kaggle. Technically, it is a binary classifier that divides clients into two groups-those who leave and those who do not. The classifier will be built using bagging algorithms like Random Forest, boosting algorithms & Neural Networks

A repository contains more than 12 common statistical machine learning algorithm implementations. 常见机器学习算法原理与实现

Project of analysis for credit card transactions, e.g. predictions of overdue risk, clustering of customer value. Real financial data and different machine learning methods applied.

This notebook explores fraud detection using various machine learning techniques.

Insanely fast Open Source Computer Vision library for ARM and x86 devices (Up to #50 times faster than OpenCV)

Investment Analysis and Asset Mgmt, Time Series Analysis & Forecasting, Machine Learning in Finance & Causal Inference Methods

Two algorithms based on linear programming to discover classification rules for interpretable learning.

Data and code for a machine learning exercise in which I predict the development of depression.

Investigate personnel elements influencing organizational dynamics by looking at HR analytics data using python and advanced machine learning models. Forecast employment status, estimate the period of termination, and maximize performance and satisfaction initiatives.