mctrinh/neural-networks-from-scratch

Neural Networks from Scratch in Python crafted for utilization as teaching resources in graduate courses (Deep Learning, Deep Learning for Computer Vision) delivered by Minh-Chien Trinh at Jeonbuk National University.

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These Jupyter notebooks help graduate students in Deep Learning and Deep Learning for Computer Vision courses understand how neural networks work from the ground up. By starting with fundamental mathematical concepts, you can build neural network components piece by piece. This provides a clear, step-by-step understanding of neural network architecture and operation for students learning the subject.

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Use this if you are a graduate student or instructor who needs to learn or teach the foundational mechanics of neural networks by building them yourself.

Not ideal if you're looking for a high-level library to implement neural networks quickly without needing to understand the underlying code.

deep-learning-education computer-vision-training neural-network-fundamentals graduate-student-resources
No License Stale 6m No Package No Dependents
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Jun 10, 2025

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