MehdiJmlkh/Deep-Learning-Course-Homeworks
Deep Learning course, Sharif University of Technology, Dr. Soleymani, Spring 2024
This collection provides practical examples and theoretical explanations for core deep learning concepts. It demonstrates how to build and train various neural networks, from basic fully connected layers to advanced models for image recognition, natural language processing, and generative tasks. Students and self-learners in computer science or related fields would find this useful for understanding deep learning fundamentals.
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Use this if you are a student or self-learner looking for hands-on, explained examples of deep learning algorithms and their applications.
Not ideal if you need a production-ready library or a tool for immediate deployment in a professional setting.
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Jupyter Notebook
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MIT
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Feb 01, 2025
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