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Learn and Predict

Welcome to the Learn and Predict repository! This repository contains a collection of projects aimed at practicing various machine learning models on different datasets to predict outcomes. Each project focuses on a specific dataset and demonstrates the application of different machine learning techniques.

Projects

1. Rock vs Mine Classification

This project explores the use of Logistic Regression to classify objects detected by sonar as either rocks or mines. A dataset containing sonar readings of various objects was used to train and evaluate the model.

  • Dataset: Sonar Object Dataset
  • Model: Logistic Regression

This project serves as a basic introduction to machine learning algorithms, focusing on data preparation, model training, and evaluation.

2. Diabetic Prediction

This project implements a Support Vector Machine (SVM) to predict whether an individual is likely to have diabetes based on a set of health-related features.

This project demonstrates the application of a classification model to a medical dataset, highlighting the potential of machine learning in healthcare.


How to Use

  1. Clone the repository:
    git clone https://github.com/yourusername/learn-and-predict.git
  2. Explore each project folder to find the dataset, code, and explanations for each model.

Future Additions

This repository will continue to grow as more machine learning models are implemented on different datasets. Stay tuned for more projects!