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Feature Description
This feature will implement the core algorithm for training neural networks without using libraries like TensorFlow or PyTorch. This 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
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Add ScreenShots
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Priority
High
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