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

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

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

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)

Slides, exercises, and exams for my course "Statistical Learning with R" (Ecole Normale Supérieure Paris-Saclay, 2023)

This project combines meticulous data preprocessing-visualization-machine learning techniques, featuring Decision Tree, integrating Logistic Regression. Prioritizes model interpretability-accuracy through feature selection, optimizing performance evaluation for species classification using sepal & petal features.

Учебные материалы по курсам связанным с Машинным обучением, которые я читаю в УрФУ. Презентации, блокноты ipynb, ссылки