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Ahmad-Ali-Rafique / repository
This project demonstrates a complete pipeline for recognizing handwritten digits using the MNIST dataset. The project is implemented in Python using Jupyter Notebook, and it covers data loading, preprocessing, model training, and performance evaluation of a Fully Connected Neural Network (FCNN).
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This project demonstrates a complete pipeline for recognizing handwritten digits using the MNIST dataset. The project is implemented in Python using Jupyter Notebook, and it covers data loading, preprocessing, model training, and performance evaluation of a Fully Connected Neural Network (FCNN).
The project uses the MNIST dataset, which consists of 70,000 images of handwritten digits (0-9) split into training and testing sets. The pipeline includes:
Hi, I'm Ahmad Ali, a passionate data scientist and machine learning enthusiast with a knack for solving complex problems using data-driven approaches. I have a strong background in data science and artificial intelligence, and I enjoy working on projects that involve deep learning, computer vision, and natural language processing.
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