https://github.com/kmohamedalie/optical-recognition-of-handwritten-digits

Recognising Handwritten digits with 98.89% accuracy, precision and f1-score
https://github.com/kmohamedalie/optical-recognition-of-handwritten-digits

computer-science handwritten-digit-recognition ibm machine-learning ocr-recognition random-forest snapml

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Recognising Handwritten digits with 98.89% accuracy, precision and f1-score

• Host: GitHub
• URL: https://github.com/kmohamedalie/optical-recognition-of-handwritten-digits
• Owner: Kmohamedalie
• License: mit
• Created: 2023-08-15T13:09:59.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2023-08-22T13:19:11.000Z (about 1 year ago)
• Last Synced: 2023-08-22T16:03:07.422Z (about 1 year ago)
• Topics: computer-science, handwritten-digit-recognition, ibm, machine-learning, ocr-recognition, random-forest, snapml
• Language: Jupyter Notebook
• Homepage: https://github.com/Kmohamedalie/Optical-Recognition-of-Handwritten-Digits
• Size: 775 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        


  

# Optical Recognition of Handwritten Digits 

  

https://github.com/Kmohamedalie/Optical-Recognition-of-Handwritten-Digits/assets/63104472/68bb58a1-8707-4f17-9786-2ec7cd2a76fe

**Source:** [IBM Technology - Optical Character Recognition (OCR)](https://www.youtube.com/watch?v=or8AcS6y1xg)

Task:
 Recognising handwritten digits using classical machine learning algorithms (Random Forest and Support Vector Machine)


### **Complete JupyterNotebook:** [Link](https://github.com/Kmohamedalie/Optical-Recognition-of-Handwritten-Digits/tree/master/Notebook)




**Metrics:**

| Algorithm | Precision | Recall  | F1-score | Accuracy |

|-----------|-----------|---------|----------|----------|

|Support Vector Machine   | 98.89%    |  98.89% | 98.89%   | 98.89%   |




What's OCR by Medium:

Handwritten digit recognition is an ability of machines to recognize human written digits or numbers. OCR[Optical Character Recognition] is one of the examples of handwritten text recognition. It is quite difficult for machines to understand or recognize human written text or numbers. The solution for this problem is programs like OCR or handwritten digit recognition programs. These programs takes image as input and converts them into machine understandable bits. And with the help of these bits, the computer recognizes the digits present in the image.