Skip to content

An Interactive Website to do hands-on Machine learning. An online platform for learning and visualizing machine learning and deep learning concepts. Here you can see algorithm in action. Examples: Read about Autoencoder and see how they work.

Notifications You must be signed in to change notification settings

Sudhanshu1304/Machine-Learns

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

47 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Machine-Learns


Link to the Website --- Click here 👈
"Note" : because of free hosting service and heavy model hosted on Heroku, the website may take quite some time to open


A platform where you learn and visualize the working of different concepts and algorithms of Machine Learning and Deep Learning. Right from basic concepts like linear regression to advanced concepts like VAE, Generative models, etc.



It is an Interactive website where you can understand and play around with Machine Learning Concepts.

You will also find Blogs on different ML & AI Concepts.



Preview


Home Page Home Page
Home Page Home Page

Getting Started

To run this project locally, follow these steps:

Prerequisites

  • Python 3.x
  • Django
  • Virtualenv (optional but recommended)

Installation

  1. Clone the repository:

    git clone https://github.com/yourusername/Machine-Learns.git
    cd Machine-Learns   ```
    
  2. Create a virtual environment (optional):

    python -m venv venv
    source venv/bin/activate  # On Windows use `venv\Scripts\activate`   ```
    
  3. Install the required packages:

    pip install -r requirements.txt   ```
    
  4. Apply migrations:

    python manage.py migrate   ```
    
  5. Run the server:

    python manage.py runserver   ```
    
  6. Access the application:

    Open your web browser and go to http://localhost:8000.

Notes

  • Ensure you have the necessary data files in the images directory as specified in the apps.py file.
  • If you encounter any issues with missing models, ensure they are placed in the Api/Models directory.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

About

An Interactive Website to do hands-on Machine learning. An online platform for learning and visualizing machine learning and deep learning concepts. Here you can see algorithm in action. Examples: Read about Autoencoder and see how they work.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published