seloufian/Deep-Learning-Computer-Vision

My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.

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This project provides comprehensive assignment solutions for two leading university courses in deep learning and computer vision: Stanford's CS231n and Michigan's EECS 498-007/598-005. It takes theoretical concepts from lectures and applies them through practical implementations, using Python with NumPy, TensorFlow, and PyTorch. The solutions are designed for machine learning practitioners and researchers who want to deepen their understanding of computer vision algorithms.

134 stars. No commits in the last 6 months.

Use this if you are studying advanced computer vision and deep learning, and want to review or compare your own solutions to well-structured, commented examples from rigorous university assignments.

Not ideal if you are a beginner with no background in machine learning, statistics, algebra, or Python programming with NumPy, as the content assumes foundational knowledge and dives into advanced topics from scratch.

deep-learning computer-vision neural-networks image-recognition machine-learning-education
No License Stale 6m No Package No Dependents
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Maturity 8 / 25
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cs231n-course-assignments

Last pushed

Apr 04, 2021

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CS231N Course Assignments · 30 frameworks

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