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.

CS-GY 6953 Deep Learning Major Project

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.

A package to evaluate 3d weather and air quality models

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.

This breast cancer diagnosis project evaluates various machine learning models to effectively classify breast masses as benign or malignant. SVM and Logistic Regression excel in identifying positive cases, leveraging their robust performance metrics, while Neural Networks show promising results and offer opportunities for further enhancement!

Quality Prediction of red and white wine

A spam detection model built to handle imbalanced data using small pipelines. This project walks through text preprocessing, model tuning, and performance evaluation with ROC-AUC curves and classification reports, focusing on practical steps like using XGBoost and TFIDF for spam classification.

Loan Approval Analysis involves building a machine learning model to predict whether a loan will be approved or not based on various customer features

🗣️ Speech Type Detection is a Flask app to classifies text into categories like "Hate Speech," "Offensive Language," or "No Hate or Offensive Language" with 87.3% accuracy. It offers a user-friendly interface for text input and prediction, using machine learning algorithms. Idea for managing online inappropriate language. 🌐🔍.

"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.

UCI Heart Disease - Feature Engineering and Models Evaluation

Coursera Applied Machine Learning in Python

Analyzed 5,000+ movies with Pandas and Colab to build a machine learning model predicting movie revenue.

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

Projeto que utiliza a base de dados Iris para calcular a acurácia e a função de perda de um modelo de aprendizado de máquina. Focado em análise de desempenho e avaliação de modelos.

About Machine Learning and Data Analysis on Diamonds Dataset

This project utilizes machine learning to address the broad problem of spam through algorithms like Multinomial Naive Bayes and Logistic Regression; it can classify incoming emails as either spam or ham. This project aims to enhance email security and user experience while minimizing the risks of phishing attacks.