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24 lines
1.2 KiB
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24 lines
1.2 KiB
Markdown
# CMU 11-785: Introduction to Deep Learning
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## Descriptions
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- Offered by: CMU
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- Prerequisites: Linear Algebra, Probability, Python Programming, and ML Foundations
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- Programming Languages: Python
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- Difficulty: 🌟🌟🌟🌟🌟
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- Class Hour: ~120 hours
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CMU 11-785 is a rigorous, fast-paced deep learning core course with very little filler. It starts from neural network fundamentals and systematically covers CNNs, RNNs, Attention/Transformers, optimization, and generalization.
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The workload feels close to graduate-level training: assignments usually require real understanding of model behavior, training details, and experimental methodology. If you want durable deep learning fundamentals (instead of only using high-level APIs), this course is an excellent investment.
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## Course Resources
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- Course Website: <https://deeplearning.cs.cmu.edu/S26/index.html>
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- Recordings: Lecture recordings are available on course websites (varies by semester)
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- Textbooks: Mainly Lecture Notes / Slides + paper readings
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- Assignments: Multiple programming assignments and a course project (published on course sites)
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## Personal Resources
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No public personal repository is currently provided for this course.
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