• kashish jain
• vishal
• tintus
• Ms richa sharma
• abhishek

The communication of ideas in today’s world is necessary and there are various symbols and characters denoting a particular meaning being used, the digits being one of them. This paper discusses the digit recognition using machine learning classifiers and comparing their performances. The input given in this case is the set of digits (0-9). And further, the model is trained using Random Forest Classifier, Naives Bayes using the Jupyter notebook in the Python language. The classifiers have been compared on various parameters, which are discussed in the paper. Though, the classifier can work only on the digits (0-9) and cannot classify more than a single digit, when given as input. In addition to that, the prerequisite is that the input digits should only be black or white in colour.

handwritten character recognition

"handwritten character recognition using python", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 3, page no.2528-2539, March-2021, Available :http://www.jetir.org/papers/JETIR2103316.pdf

"handwritten character recognition using python", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp2528-2539, March-2021, Available at : http://www.jetir.org/papers/JETIR2103316.pdf