Course Material for Artificial Intelligence and Machine Learning - Unit 2 @ Computer Science Dept, Sapienza

A repository housing machine learning projects curated by Tejas, highlighting diverse applications, methodologies, and implementations in Python.

This repository contains implementations of various machine learning algorithms from scratch (KNN, MSE Linear Regression, SVM, Neural Networks, Logistic Regression). Each algorithm is implemented in Python and is contained in its own directory.

Credit Scoring Project: Perform a Weight of Evidence Logistic Regression Modelling (WoELR) to generate credit scorecard for credit/ loan approval.

Loan Eligibility Prediction Model: A machine learning application to predict loan approval based on applicant data. Includes a web interface for submitting loan applications and receiving predictions. Built with Python and Jupyter Notebook.

A collection of 8 Applied Data Science projects.

Educational notebooks reviewing machine learning models and concepts.

Simple and flexible classical ML module that can be used for recording baseline ML performance.

A machine learning project to predict breast cancer using logistic regression. This project includes data preprocessing, feature scaling, model training, and evaluation, based on a guided project from Coursera.

A predictor of GPCR couplings with G-proteins/B-arrs using Transformers

This project demonstrates email classification using logistic regression.

This repository is about a trained Machine Learning model which predicts Whether the Heart Disease is present or not by considering few factors. This ML model is selected by considering different accuracies of various trained ML models.

Predict and prevent customer churn in the telecom industry with this project. Leverage advanced analytics and ML on a diverse dataset to build a robust classification model. Gain a deep understanding of customer behavior and identify key factors influencing churn. Clone the repository, explore insights, and enhance customer retention startegies.

Created a Linear Regression based Machine Learning Model to predict whether an mail is a spam mail or a ham mail

AI model used to predict Bitcoin closing price over 1-minute intervals

How to Spot a (Russian) Troll - Classifying Troll Tweets vs Authentic Tweets

Slides, exercises, and exams for my course "Natural Language Processing" (École Pour l'Informatique et les Techniques Avancées, 2024)