Handwritten Digit Recognition using Machine Learning
Handwritten Digit Recognition System developed using Python Programming Language and User Interface designed using Django, when user run the python script the program will generate one URL, user have to copy and paste that URL in any browser and home page will open and in that particular space user have to draw any number from mouse cursor and click on guess button to predict that particular number.
Project Flow of Handwritten Digit Recognition:-
• Preprocessing: Standardizes and enhances image features.
• CNN Architecture: Utilizes CNN for spatial feature learning.
• Training: Learns from labeled digit data.
• Optimization: Adjusts internal parameters using optimization algorithms.
• Feature Extraction: Learns patterns and relationships within images.
• Classification: Accurately categorizes new digit images.
• Applications: Enables optical character recognition and digit analysis.
Handwritten Digit Recognition using Neural Network
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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