Various data structure implementations in Python

AI Game experiments using Machine Learning and Reinforcement Learning

A classification model built using Logistic Regression to predict survival outcomes on the Titanic Dataset. The project includes feature encoding, feature scaling, model evaluation, and ROC-AUC analysis using Python ML tools.

This project implements a Disease Prediction System using various machine learning algorithms to predict potential diseases based on user-provided symptoms. The system utilizes a Django web framework to provide a user-friendly interface for inputting symptoms and viewing the predicted disease.

Machine Learning algorithms implemented from scratch. Different ML algorithms implemented from scratch. Namely, Multipile Linear Regression and Logistic Regression KNN and Naive Bayes Recrusive Decision Trees Bagging and Boosting (Ada Boost) Yarwosky's Algorithm and Agglomerative Hierarchical Clustering

This is the second project in University of Tehran College of Engineering AI course.