ML_Training

Overview

This repository contains Jupyter Notebooks related to Machine Learning training. It includes various notebooks that cover different aspects of machine learning, from basic concepts to advanced techniques.

Installation

To run the notebooks in this repository, you need to have Python and Jupyter Notebook installed. You can install the required dependencies using pip:

pip install -r requirements.txt

Usage

1. Clone the repository:

   git clone https://github.com/ayudixit/ML_Training.git
   cd ML_Training

2. Start Jupyter Notebook:

   jupyter notebook

3. Open any notebook to start learning and experimenting with machine learning concepts.

The following Jupyter Notebook files in the repository ayudixit/ML_Training are listed according to their modified dates:

1. Basic_ChatBot.ipynb: "Rename Lab1.ipynb to Basic_ChatBot.ipynb"
2. Stock_Prediction.ipynb: "Created using Colab"
3. Heart_Disease_Predictor.ipynb: "Using Logistic Regression"
4. Stock_Prediction.ipynb: "Using Logistic Regression"
5. K_Means_Clustering_For_Student.ipynb: "K-Means Clustring"
6. K_means_clustering_&_Hierarchical_Clustering_Dendrogram.ipynb: "Hirerarical Clustering Dendrogram"

Please refer to these links for more details on the modifications.

Contributing

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add some feature').
5. Push to the branch (git push origin feature-branch).
6. Create a new Pull Request.

License

This project is licensed under the MIT License. See the LICENSE file for details.