StyleGAN2-ADA trained on a dataset of 2000+ sneaker images

Home Loan Approval Prediction System uses machine learning to predict loan approval outcomes, helping financial institutions streamline decisions. It preprocesses data, handles missing values, encodes features, and uses a Random Forest Classifier for feature selection, optimizing the model for accuracy and efficiency.

Body Area Network (BAN) This repository implements a machine learning model for anomaly detection in body sensor data collected through a Body Area Network (BAN). The model analyzes heart rate and body temperature readings to identify potential health concerns.

Quantifying Integrity in the Digital Age Misinformation spreads rapidly, accountability often falters, and the lines between transparency and manipulation blur

Fertilizer prediction Api (https://predict-fertilizer-api.onrender.com/predict)

The project was built with data handling performed through Pandas and NumPy for efficient manipulation of environmental datasets. Machine learning models, including Linear Regression and Random Forest Regressor, were implemented using Scikit-learn. Model performance was evaluated using metrics like R² Score, MAE, RMSE.Trained modules were in .pkl .

Deploy a machine-learning web app that makes predictions based on data using Python and Flask.

This project focuses on analyzing a dataset comprising records of patients diagnosed with liver diseases and those without. The goal is to explore the data, identify meaningful patterns, and build predictive models to support early diagnosis, ultimately contributing to improved healthcare outcomes.

This project aims to detect fraudulent credit card transactions using a machine learning model. The application is built using Flask for the backend and a simple HTML form for the frontend. The model predicts fraud based on the Time and Amount features of the transaction.

Training model to predict passenger survival.

ML Project

Pkl schema/template generation for @moonrepo/moon

ML-Based Disease Prediction and Medical Recommendation Web App

Sentiment Analysis For Restaurant Reviews

This repository contains a machine learning model for classifying waste types (organic & inorganic), along with a Flask-based REST API for backend integration in the Trash to Cash platform.

Problem Statement: Financial institutions face significant challenges in detecting fraudulent activities due to the large volume of transactions and the sophistication of modern fraud techniques. The problem is to design AI models that can accurately detect fraudulent transactions in real-time while minimizing false positives.

Excited to announce that I’ve successfully created a AI Agent using Machine Learning for our website! 🤖✨ It's designed to enhance user interaction and provide seamless support. 🌐💬 #NovaNectar #Chatbot #MachineLearning #Innovation 🚀

This repository contains a machine learning model built to detect fake news articles. The project leverages natural language processing techniques and a supervised learning approach to classify news articles as either real or fake based on their content.