Handwritten Digit Recognition

[alo7lika]

#106 The proposed solution for the Handwritten Digit Recognition project involves developing a convolutional neural network (CNN) model that leverages the capabilities of TensorFlow and Keras to accurately classify handwritten digits from the MNIST dataset. The solution will consist of several key components: data preprocessing to normalize and augment the dataset for improved model training; the architecture of the CNN, which will include convolutional layers for feature extraction, pooling layers for dimensionality reduction, and fully connected layers for final classification; and a training process that utilizes appropriate loss functions and optimization algorithms to enhance model performance. Additionally, the solution will include evaluation metrics to assess the model's accuracy and loss on both the training and validation datasets, ensuring that it generalizes well to new data. By employing this structured approach, the model aims to achieve high accuracy in recognizing handwritten digits, ultimately providing an efficient tool for applications that require digit recognition.

[github-actions]

Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊

[SaiNivedh26]

@alo7lika You're trying to push 2 different projects at a same time. It's not a good practice.
Only raise Seperately for the issue which you've raised.

Please raise according