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Handwritten digit recognition is the ability of a computer system to identify and process handwritten numbers. This is typically done using machine learning algorithms that are trained on a large dataset of labeled images. The goal of this project is to accurately classify the digits in order to make them easier for humans to read.

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vanshj22/Handwritten-Digit-Recognition-ml

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Handwritten-Digit-Recognition-ml

Handwritten digit recognition is the ability of a computer system to identify and process handwritten digits, such as those found on a check or a piece of paper with a phone number on it. This will be done using machine learning algorithms such as the random forest classifier, tensorflow, support vector classifier etc. and image processing techniques. The goal of the system is to accurately classify the handwritten digits in order to make them easier for humans to read and understand.

rfc - random forest classifier svc - support vector classifier tf - tensorflow

Dataset used - https://www.kaggle.com/competitions/digit-recognizer/data

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Handwritten digit recognition is the ability of a computer system to identify and process handwritten numbers. This is typically done using machine learning algorithms that are trained on a large dataset of labeled images. The goal of this project is to accurately classify the digits in order to make them easier for humans to read.

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