This repository is for a final group project of a course only.

This was a project from Coursera. In this we had to predict heart diseases using the given dataset

Analyizing the effect that qualitative predictors have on sales.

In this data set we have perform classification or clustering and predict the intention of the Online Customers Purchasing Intention. The data set was formed so that each session would belong to a different user in a 1-year period to avoid any tendency to a specific campaign, special day, user profile, or period.

Predicting bug reassigned fields using stack traces and ensemble of multiple HMM classifiers.

TFM Luis González - Pavla Fuxova

Predicting amount of funding the NIH awarded research grants (R01s)

Predicting the percentage of student based on the study hour using simple linear regression.

Predicting Parkinson decease using decision trees

# the predictions may change according to different reasons. the predictions may change the 97% accuracy this shows may change the predictions may change

Set of R codes on Data Cleaning , Analysis and Interpretation. Running Linear and Logistic Regressions and doing classification in R.

Project 3 of Term 1 in the Udacity Self Driving Car Nanodegree

This project aims to detect fake news using machine learning techniques. It utilizes a machine learning model that classifies news articles as real or fake based on their content.

the predictions may. Accuracy : 52.5% not sure the predictions may change.

☣A Hac'KP initiative where Crime profiling can be done using AI☣

Predicting safe-incident and unsafe-incident neighborhoods, based on number of incidents like fire, gas-leaking response time and etc can be useful for consult cities and the residents to be aware of the fire department's facilities.

Heat Index Forecasting for different Regions in the Philippines. The link is currently not working because we have to shutdown the API as it can cost us a lot of money. NOTE: this project was made for mobile web browsers, so the design might not be that responsive if viewed on desktop.