jeffheaton/t81_558_deep_learning resource

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5734 stars · 2968 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A university course repository (T81-558, Washington University in St. Louis) containing full Jupyter notebook materials for applying deep neural networks with TensorFlow/Keras. It covers CNNs, LSTMs, GANs, reinforcement learning, and applications in vision, NLP, and time series, and is superseded by a newer PyTorch version of the course.

Use cases

• learn deep learning with Keras and TensorFlow
• self-study neural networks with Jupyter notebooks
• understand CNNs, LSTMs, and GANs through examples
• find a structured deep learning course with videos and workbooks
• learn reinforcement learning and NLP applications of neural networks
• get course materials for teaching applied deep learning

When to choose

• you want a free, comprehensive, notebook-based deep learning curriculum
• you prefer learning with TensorFlow/Keras
• you want lecture videos plus hands-on workbooks
• you are a beginner with some programming background but no Python experience

When to avoid

• you want the current PyTorch version of this course (use app_deep_learning instead)
• you need a production library or tool rather than educational material
• you need cutting-edge, frequently updated content
• you require a permissively licensed codebase you can redistribute

Facets

learning-resource · maturity maintenance

deep-learning machine-learning deep-learning machine-learning tutorials computer-vision python keras tensorflow jupyter-notebooks university-course gan cnn reinforcement-learning course-materials natural-language-processing

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