Python
Diagnosis of Liver Disease using ANN and MLAlgorithms with Hyperparameter Tuning
The aim of this project is to develop a system for the diagnosis of liver disease using Artificial Neural Networks (ANN) and Machine Learning (ML) algorithms with hyperparameter tuning. The project focuses on leveraging advanced models and optimization techniques to enhance predictive capabilities, aiding in the early detection and effective management of liver disease.
DOC-BLOCK: A Blockchain Based Authentication System for Digital Documents
Driver-Drowsiness Detection System Using Facial Features
DroneGuard: An Explainable and Efficient Machine Learning Framework for Intrusion Detection in Drone Networks
Drought Forecasting: Application of Ensemble and Advanced Machine Learning Approaches
E-Commerce Fraud Detection Using Generated Data From BANKSIM Using Machine Learning
E-commerce Products Image Classification using EfficientNetB5 with Transfer Learning
Early Detection of Childhood Malnutrition using Survey Data and Machine Learning Approaches
Edge Fire Smoke A novel lightweight cnn model for Real Time video Fire smoke Detection
Efficient Classification Of Diabetic Retinopathy Using Binary Cnn
Efficient Machine Learning Approach For Crime Detection In India
The goal of this project is to create a reliable model for predicting droughts in regions that are vulnerable to them. Using Indian rainfall data, the project applies ARIMA and SARIMAX models to forecast droughts. The project aims to support better planning and response strategies, helping communities prepare for and mitigate the effects of droughts.
