Machine Learning Repository

This repository contains Jupyter Notebook programs implementing various machine learning algorithms. Each algorithm is designed to solve specific types of problems, and the accompanying datasets are provided for experimentation.

Algorithms Implemented

1. Linear Regression

• Description: This notebook implements a simple linear regression model using a sample dataset.

2. Logistic Regression

• Description: Implementation of logistic regression for binary classification, using a dataset with labeled examples.

3. Random Forest Classifier

• Description: Implementation of a random forest classifier for classification tasks. The notebook includes training and evaluation on a dataset.

4. Neural Network

• Description: Introduction to neural networks using a simple architecture. The notebook includes training and testing on a dataset suitable for a neural network.

5. Support Vector Machine (SVM)

• Description: Implementation of a Support Vector Machine for classification tasks. The notebook includes tr

How to Use

1. Clone the repository:

   git clone https://github.com/Sumanth007/ML.git

2.Install Jupyter Notebook:

pip install jupyter

3.Navigate to the cloned repository and start Jupyter Notebook:

You can directly run this using Anaconda Navigator