Volume- 8
Issue- 4
Year- 2020
DOI: 10.21276/ijircst.2020.8.4.16 |
DOI URL: https://doi.org/10.21276/ijircst.2020.8.4.16
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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)
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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.
Student, B.Tech, Department of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India (email: pranitp2222@gmail.com)
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