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The ML project uses Linear Regression to predict the trip time of a bike rental for a new prediction system in new mobile application. The ML datasets have been collected and stored in a BigQuery public dataset
Comprehensive analysis and modeling of the Wine Quality dataset, including exploratory data analysis (EDA), data preprocessing, model training, and performance evaluation using MSE and RMSE.
This repository contains a machine learning project for email spam detection. It includes data preprocessing, model training, evaluation, and deployment using Python and scikit-learn.
This repository consist of machine learning models which can be use for predicting the future instance. More specifically this repository is a Machine Learning course for those who are interested in learning the basics of machine learning algorithms.
This project is created using Machine Learning and Regression methods- a statistical technique to predict the outcome of event which is to verify the users’ admission eligibility level, considering the universities they have chosen. This is achieved based on the algorithms implemented, when is user feed the application with the required information
In this Machine learning project I have selected three diseases for predict status. The disease are Kidney Disease prediction, Heart Disease prediction and Diabetes disease prediction.
This toolkit is a curated collection of machine learning projects, resources, and utilities designed to assist both beginners and seasoned practitioners in their journey through the fascinating world of machine learning.