HzcIrving/DLRL-PlayGround
The code repo contains multiple code reproduction processes of various SOTA deep learning algorithms
This collection provides ready-to-use examples and code for various cutting-edge deep learning and reinforcement learning algorithms. It helps machine learning engineers and researchers quickly experiment with and understand complex models like Transformers for image classification (e.g., Vision Transformer, Swin Transformer) and offline reinforcement learning techniques (e.g., Decision Transformer, BCQ). You can take an input like an image and get a classification, or use recorded data to train an agent.
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Use this if you are a machine learning engineer or researcher looking for hands-on, reproducible code implementations of state-of-the-art deep learning and reinforcement learning models.
Not ideal if you are looking for a high-level API or a user-friendly application to solve a specific business problem without needing to interact with the underlying model code.
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Jupyter Notebook
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MIT
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Last pushed
Mar 22, 2022
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