MNIST Digit Recognition Project

Overview

This repository contains a complete MNIST digit recognition project that includes a Streamlit dashboard, a neural network model, and a Jupyter notebook. The project demonstrates the end-to-end process of training a neural network on the MNIST dataset and deploying it through a user-friendly interface.

Project Structure

• app.py: Streamlit application for interactive digit recognition.
• mnist_model.h5: Trained neural network model saved in HDF5 format.
• mnist_digit_recognition_notebook.ipynb: Jupyter notebook for data exploration, model training, and evaluation.
• requirements.txt: List of Python packages required to run the project.
• data/: Directory for storing any dataset files (if needed).
• images/: Directory for storing images like profile pictures.

Model Information

The MNIST Digit Recognition model is a feedforward neural network trained on the MNIST dataset, which consists of handwritten digits from 0 to 9. Key model details:

• Model Type: Feedforward Neural Network
• Architecture: 2 Hidden Layers
• Activation Functions: ReLU (Hidden Layers), Softmax (Output Layer)
• Training Epochs: 15
• Batch Size: 200

How to Run the Dashboard

1. Clone the Repository:

   git clone https://github.com/yourusername/mnist-digit-recognition-project.git

2. Navigate to the Project Directory:

   cd mnist-digit-recognition-project

3. Install Dependencies: Create a requirements.txt file with the following content:

   streamlit
   tensorflow
   pillow
   numpy
   matplotlib
   jupyter
   

   Install the dependencies using pip:

   pip install -r requirements.txt

4. Run the Streamlit App:

   streamlit run app.py

How to Use the Jupyter Notebook

1. Install Jupyter Notebook (if not installed):

   pip install jupyter

2. Open the Notebook:

   jupyter notebook mnist_digit_recognition_notebook.ipynb

3. Run the Cells: Follow the instructions in the notebook to explore the data, train the model, and evaluate performance.

About Me

Ahmad Ali Rafique
AI & Machine Learning Specialist

I am an AI and Machine Learning specialist dedicated to developing innovative solutions using advanced machine learning techniques. My expertise includes building and deploying models for various applications, with a focus on creating impactful and user-friendly solutions.

Contact Information

• LinkedIn
• GitHub
• Email

Feel free to connect with me or reach out if you have any questions or opportunities for collaboration!