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This project focuses on the detection of myocardial infarction (heart attack) using machine learning techniques. We leverage the PTB diagnostic database, a widely used dataset in the field of cardiology.
This repo consists of data visualization project done for wealth management dataset from Kaggle. I have used various Machine Learning classifiers to calculate accuracy and precision to determine which model works best for this dataset. The agenda of this project is to analyze the trend of customer churn from a wealth management company.
Minor project for disease prediction using machine learning classifiers such as logistic regression, decision tree, random forest, and MLP (Multi-layer Perceptron). The project focuses on evaluating the performance of these classifiers based on accuracy, confusion matrices, and classification reports.
Tumor prediction from microarray data using 10 machine learning classifiers. Feature extraction from microarray data using various feature extraction algorithms.
The purpose of the Sign-Interfaced Machine Operating Network, or SIMON, is to develop a machine learning classifier that translates a discrete set of ASL sign language presentations from images of a hand into a response from another system.