| 1 | Title of the Article | Handwritten Digit Recognition Using Various Machine Learning Algorithms and Models |
| 2 | Author's name | Pranit Patil: Student, B.Tech, Department of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, India (email: pranitp2222@gmail.com) |
| 3 | Author's name | Bhupinder Kaur |
| 4 | Subject | Computer Science and Engineering |
| 5 | Keyword(s) | Convolutional Neural Network, Support Vector Machine, HandWritten Digit Recognition, Artificial Intelligence, Deep Learning. |
| 6 | Abstract | 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. |
| 7 | Publisher | Innovative Research Publication |
| 8 | Journal Name; vol., no. | International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-8 Issue-4 |
| 9 | Publication Date | July 2020 |
| 10 | Type | Peer-reviewed Article |
| 11 | Format | |
| 12 | Uniform Resource Identifier | https://ijircst.org/view_abstract.php?title=Handwritten-Digit-Recognition-Using-Various-Machine-Learning-Algorithms-and-Models&year=2020&vol=8&primary=QVJULTUzOQ== |
| 13 | Digital Object Identifier(DOI) | 10.21276/ijircst.2020.8.4.16 https://doi.org/10.21276/ijircst.2020.8.4.16 |
| 14 | Language | English |
| 15 | Page No | 337-340 |