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[Feature Request]: Adding backpropogation in Deep Learning #3129

Closed Shantnu-singh closed 3 months ago

Shantnu-singh commented 3 months ago

Is there an existing issue for this?

Feature Description

This feature will ensure hands-on approach helps users understand the mechanics of backpropagation, including gradient descent, weight updates, and error calculation, offering a deeper insight into how neural networks learn.

Use Case

Ideal for students, educators, and developers, this feature provides a clear understanding of neural network training. Students can explore the step-by-step process, educators can demonstrate the algorithm in classes, and developers can build custom solutions, enhancing their knowledge and flexibility in neural network design.

Benefits

No response

Add ScreenShots

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Priority

High

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github-actions[bot] commented 3 months ago

Hi @Shantnu-singh! 👋 Thank you for opening your first issue on CodeHarborHub. We're excited to hear your thoughts and help you out. You've raised a great topic! Please provide as much detail as you can so we can assist you effectively. Welcome aboard!

github-actions[bot] commented 3 months ago

Hi @Shantnu-singh! Thanks for opening this issue. We appreciate your contribution to this open-source project. Your input is valuable and we aim to respond or assign your issue as soon as possible. Thanks again!

github-actions[bot] commented 3 months ago

Hello @Shantnu-singh! Your issue #3129 has been closed. Thank you for your contribution!