IJIRCST

Handwritten Digit Recognition Using Various Machine Learning Algorithms and Models

Pranit Patil | Bhupinder Kaur

Handwritten digit recognition is a technique or technology for automatically recognizing and detecting handwritten digital data through different Machine Learning models. In this paper we use various Machine Learning algorithms to enhance the productiveness of technique and reduce the complexity using various models. Machine Learning is an application of Artificial Intelligence that learns from previous experience and improves automatically through experience. We illustrate various Machine learning algorithms such as Support Vector Machine, Convolutional Neural Network, Quantum Computing, K-Nearest Neighbor Algorithm, Deep Learning used in Recognition technique.

Convolutional Neural Network, Support Vector Machine, HandWritten Digit Recognition, Artificial Intelligence, Deep Learning.

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[Pranit Patil, Bhupinder Kaur (2020), Handwritten Digit Recognition Using Various Machine Learning Algorithms and Models, International Journal of Innovative Research in Computer Science & Technology (IJIRCST), Vol-8, Issue-4, Page No-337-340], (ISSN 2347 - 5552). www.ijircst.org

Pranit Patil

Student, B.Tech, Department of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India (email: pranitp2222@gmail.com)

DOI:

DOI: 10.21276/ijircst.2020.8.4.16 DOI URL: https://doi.org/10.21276/ijircst.2020.8.4.16

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)