Liver Disease prediction with 99% accuracy using Convolutional Neural Network and ML model

Introduction: As a final year student, choosing a compelling and impactful project is crucial for showcasing your skills and knowledge. Liver disease prediction with 99% accuracy is good to choose, an area of growing significance in the healthcare field, offers Read more

Snake venom and non-venom classification using deep learning

Snakebite envenomation is a pressing global health issue, causing numerous fatalities and disabilities each year. Prompt identification of venomous snakes is crucial for appropriate medical intervention. Traditional venom classification methods are time-consuming and invasive, highlighting the need for efficient and non-invasive approaches. Convolutional Neural Networks (CNNs), known for their image classification prowess, offer a promising solution. By training a CNN model on a diverse dataset of snake images, this study aims to develop a robust venom classification system. Such a system could revolutionize snakebite management, improving clinical outcomes and aiding in species conservation. The implementation of CNN-based venom classification has the potential to save lives, enhance healthcare decision-making, and protect endangered snake species.

Stock Price Prediction using Hyper tuned ML models

Stock price prediction has long been a challenging problem in the financial industry, with researchers and practitioners continuously seeking more accurate and robust methods. This study explores the application of hyperparameter-tuned machine learning (ML) models for stock price prediction. Leveraging Read more