Digit-Recognition-using-CNN
Content
Digit Recognition using CNN and TensorFlow.
About The Dataset
The data files train.csv and test.csv contain gray-scale images of hand-drawn digits, from zero through nine.
Each image is 28 pixels in height and 28 pixels in width, for a total of 784 pixels in total. Each pixel has a single pixel-value associated with it, indicating the lightness or darkness of that pixel, with higher numbers meaning darker. This pixel-value is an integer between 0 and 255, inclusive.
The training data set, (train.csv), has 785 columns. The first column, called "label", is the digit that was drawn by the user. The rest of the columns contain the pixel-values of the associated image.
Getting started
- get the code from the repository and run the following command
git clone https://github.com/sagnikghoshcr7/Digit-Recognition-using-CNN.git
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Extract the Dataset.rar file or download the dataset from here
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install required python packages if previously not installed
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Finally run on Jupyter Notebook and enjoy 😉