Feature request: Add New Project - Image Classification using CNN (CIFAR-10 Dataset) under the Neural Networks Folder

[sanyadureja]

Is your feature request related to a problem? Please describe. Currently, the Neural Networks folder lacks a comprehensive example of image classification using Convolutional Neural Networks (CNNs) on standard datasets. Beginners often find it challenging to understand CNNs without practical, hands-on examples, especially on widely-used datasets like CIFAR-10.

Describe the solution you'd like I would like to add a project under the Neural Networks folder that demonstrates image classification using CNNs, specifically utilizing the CIFAR-10 dataset. This will serve as an accessible introduction to CNN architecture for users, showcasing essential concepts such as convolutional layers, pooling, activation functions, and model evaluation.

Describe alternatives you've considered An alternative would be to implement image classification on a simpler dataset (e.g., MNIST) or a more complex one (e.g., ImageNet). However, CIFAR-10 provides a balanced intermediate level, allowing users to understand CNNs without an overwhelming amount of data or complexity.

Approach to be followed (optional)

• Load and preprocess the CIFAR-10 dataset.
• Build a CNN model using layers such as Conv2D, MaxPooling2D, Flatten, and Dense.
• Compile the model, specifying the optimizer, loss function, and evaluation metrics.
• Train the model on the CIFAR-10 training data and validate it on test data.
• Evaluate the model’s performance, and provide visualizations of sample predictions.
• Document the code to guide users through the steps.

Additional context This feature would enhance the Neural Networks folder by providing a hands-on, structured introduction to CNNs, helping users understand how to apply deep learning to image classification tasks. A sample architecture or learning curves could be included to visually aid understanding.

[github-actions[bot]]

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[sanyadureja]

@Neilblaze @SaiNivedh26 @UppuluriKalyani starting to work on this issue.

[sanyadureja]

@UppuluriKalyani, @Neilblaze, and @SaiNivedh26 please review my PR https://github.com/UppuluriKalyani/ML-Nexus/pull/823 . I've solved the issue https://github.com/UppuluriKalyani/ML-Nexus/issues/822 Looking forward to getting the PR merged and assignment of level and labels.

Awaiting your response. Thank you!

[github-actions[bot]]

Hello @sanyadureja! Your issue #822 has been closed. Thank you for your contribution!