Successfully developed a language detection transformer model that can accurately recognize the language in which any given text is written.
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Updated
Dec 21, 2022 - Jupyter Notebook
Successfully developed a language detection transformer model that can accurately recognize the language in which any given text is written.
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
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 project is designed for personal learning and exploration of fundamental machine learning concepts.
🔍 Evaluating Sampling Techniques for Healthcare Insurance Fraud Detection in Imbalanced Dataset.
This repository contains codes, datasets, results, and reports of a machine learning project on air quality prediction.
random forest classification (with hyperparameter tuning) on heart disease dataset.
Quality Prediction of red and white wine
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."
E-Commerce Customer Churn Prediction using Machine Learning
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!
"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.
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)
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.
The primary objective of this study is to develop a dependable and precise prediction model to forecast alterations in Bitcoin's hash rate.
This project explores machine learning techniques, focusing on data preprocessing, model building, and evaluation. It includes data analysis, visualization, various algorithms, and performance comparison. Key topics: data cleaning, feature engineering, model selection, hyperparameter tuning, and evaluation metrics.
Summary Evaluation Tool
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