Evaluate custom and HuggingFace text-to-image/zero-shot-image-classification models like CLIP, SigLIP, DFN5B, and EVA-CLIP. Metrics include Zero-shot accuracy, Linear Probe, Image retrieval, and KNN accuracy.

Successfully developed a language detection transformer model that can accurately recognize the language in which any given text is written.

This repository contains a project showcasing Federated Learning using the EMNIST dataset. Federated Learning is a privacy-preserving machine learning approach that allows a model to be trained across multiple decentralized devices or servers holding local data samples, without exchanging them.

This repository contains codes, datasets, results, and reports of a machine learning project on air quality prediction.

Successfully established a machine learning model which can determine whether an individual is vulnerable to the Cirrhosis disease or not by predicting its corresponding stage based on a unique set of medical features such as Cholesterol, Prothrombin, etc. pertaining to that person.

About Machine Learning and Data Analysis on Diamonds Dataset

Summary Evaluation Tool

Quality Prediction of red and white wine

"Linear Regression Step by Step" is a repository that provides a comprehensive notebook with step-by-step examples, exercises and libraries to understand and implement Linear Regression easily.

Coursera Applied Machine Learning in Python

🔍 Evaluating Sampling Techniques for Healthcare Insurance Fraud Detection in Imbalanced Dataset.

This project is designed for personal learning and exploration of fundamental machine learning concepts.

E-Commerce Customer Churn Prediction using Machine Learning

The primary objective of this study is to develop a dependable and precise prediction model to forecast alterations in Bitcoin's hash rate.

Support Vector Machine Classification model is applied on bank dataset containing 41188 rows and 21 columns. The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to assess if the product (b…

"Retail transaction fraud detection project with machine learning models on the Data Mining Cup 2019 dataset."

random forest classification (with hyperparameter tuning) on heart disease dataset.

Expérimentations sur divers modèles et méthodes de Machine Learning pour la classification de textes, et étude des mesures d'évaluation des modèles après normalisation des données

An ML-based project designed to accurately classify email messages as either spam or ham (non-spam)

Predict the Class of Iris Species