Group 1 Internship Project

Handwritten-Digit-Recognition

Infosys Springboard - Handwritten Digit Recognition with LeNet5 Model in PyTorch

Infosys Springboard

An Internship project of Infosys in the feild of Artificial Intelligence, on Handwritten Digit Recognition Using various Deep learnig Architecture and then deploying the model

Features

Trying various deep learnig models Improving model accuracy Deploying all models together in one web app Making evaluation Report of the project

Tech

We uses a number of open source projects to work properly:

• LeNet-5 - A Simple CNN Architecture
• PyTorch - A Machine Learning Library
• MNIST - Modified National Institute of Standards and Technology database Containing Handwritten Digits
• Extended MNIST - EMNIST Dataset Is A Set of Handwritten Character Digit
• CNN - Convolutional Neural Network Architecture
• MLP - Multilayer Perceptron
• Flask - A Backend Micro-Framework Written In Python For The Rapid Development Process
• Docker - A software platform to build, test, and deploy applications quickly

Installation

import Libraries as according_to_project :

• PyTorch
• Numpy
• Pandas
• Matplotlib
• Flask

OR

Install the dependencies as :

pip install -r requirements.txt

Website

Check out our website Where we have deployed our project's model.

Team

Countributers and Teammate in this project

Members	[Github]	[LinkedIn]
Akhil Jain	https://github.com/AkhilJain5	https://www.linkedin.com/in/akhil-jain-61107122a/
Sachin Rajawat	https://github.com/Sachin-71	https://www.linkedin.com/in/sachin-rajawat-119ba4237/
Pranav Gupta	https://github.com/pranav412-code	https://www.linkedin.com/in/pranav-gupta-45724b22a/
Sarang Kishor Masurkar	https://github.com/SarangMasurkar	https://www.linkedin.com/in/sarang-masurkar-643819246
Shahnaz Ali	https://github.com/S-ali24	https://www.linkedin.com/in/s-ali-3439b2314?trk=contact-info