Digit Guesser

Machine learning from the browser; served from the Internet Computer Blockchain.

📚 Description

Digit Guesser is a web application that demonstrates machine learning inference taking place directly in the browser. It uses a Support Vector Machine (SVM) classifier to predict hand-drawn digits. The application is built with Vue.js and leverages Pyodide to run Python code, including scikit-learn, in the browser using WebAssembly. The application is served directly from the Internet Computer Blockchain.

✅ Features

• Draw digits using an interactive canvas
• Real-time prediction of drawn digits using a pre-trained SVM model
• Client-side machine learning powered by Pyodide
• Served directly from the Internet Computer Blockchain

🛠️ Tech Stack

• Frontend: Vue.js, JavaScript
• Machine Learning: Python, scikit-learn, scikit-image
• In-Browser Python: Pyodide

🌟 Live Demo

Experience Digit Guesser in action:

https://avtg3-4iaaa-aaaal-ajqhq-cai.icp0.io/

🏗️ Local Development

To set up the project locally:

1. Clone the repository

2. Install dependencies:

   pnpm install

3. Compile and hot-reload for development:

   pnpm run serve

4. Compile and minify for production:

   pnpm run build

🧠 Machine Learning Model

The SVM classifier used in this project is trained on the MNIST dataset. For details on how the model was trained and exported, see the train_model.ipynb notebook.

📄 License

This project is open source and available under the MIT License.

🔗 Links and Resources

• Pyodide: A Python distribution for the browser and Node.js based on WebAssembly. This project uses Pyodide to run Python code, including scikit-learn, directly in the browser.

• Juno: The Web3 development platform used for hosting and deploying this application. Juno provides blockchain-based storage and hosting solutions on the Internet Computer.

• Internet Computer: The underlying blockchain infrastructure powering this application. It provides a decentralized cloud platform for building and hosting applications like Digit Guesser.

• scikit-learn: A machine learning library for Python. In this project, it's used to train and deploy the SVM classifier for digit recognition.

• MNIST Dataset: The dataset used to train the SVM classifier in this project. It's a large database of handwritten digits commonly used for training various image processing systems.