yao-jason/ADL2019

Applied Deep Learning (2019 Spring) @ NTU

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This resource provides foundational code examples and explanations for key deep learning tasks. It takes raw text data or environmental observations and processes them to produce dialogue models, contextual embeddings for text, reinforcement learning agents, and generated images. This is for researchers or students learning and applying advanced deep learning techniques in natural language processing and artificial intelligence.

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Use this if you are a student or researcher looking for practical implementations and structured homework assignments for a university-level deep learning course.

Not ideal if you are a practitioner seeking a ready-to-use tool or a deployed solution for a specific business problem, as this is primarily educational material.

deep-learning-education dialogue-systems natural-language-processing reinforcement-learning generative-modeling
No License Stale 6m No Package No Dependents
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Adoption 6 / 25
Maturity 8 / 25
Community 16 / 25

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Last pushed

Jun 09, 2019

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