This project has the aim to analyze the Heart Disease dataset to build a classifiers to predict whether people have heart disease or not.
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Updated
Feb 24, 2022 - R
This project has the aim to analyze the Heart Disease dataset to build a classifiers to predict whether people have heart disease or not.
This project employs ensemble learning methods to forecast cybercrime rates, utilizing datasets with population, internet subscriptions, and crime incidents. By analyzing trends and employing metrics like R2 Score and Mean Squared Error, it aims to enhance prediction accuracy and provide insights for effective prevention strategies.
Implementation of Machine Learning Algorithms in python from scratch
Investigations into the credit default dataset
U of Chicago Master-Track Final Project
This project uses ML Classification models to predict Election Exit Polls and Text Mining with NLTK to analyse US Presidents' Speeches
The goal of the Hackathon is to predict whether a passenger was satisfied or not considering his/her overall experience of traveling on the Shinkansen Bullet Train.
A machine learning application, deployed using Flask, is designed to identify the presence of kidney disease in patients by analyzing various medical features.
Application for Prediction of Acute Liver Failure using Machine Learning Algorithm.
Adaptive Boosting of Weak Learners implemented in Python
This project aims to analyze the heart failure dataset to build a classifier that identifies the most important factors and allows predicting death from heart failure.
Applies Machine Learning approach to predict spam.
Predict the level of solar radiation based on dataset given from NASA
This repository includes the scripts to replicate the results of my WORKING paper entitled "A Machine Learning Approach to Detect Accounting Frauds".
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