The website introduces a suite of deep learning tools we have developed for learning patterns and making predictions on discrete data, like text, graph, or sets. Feel free to submit pull requests when you find my typos.

Background of Representation Learning and Deep Learning

The performance of machine learning algorithms is largely dependent on the data representation (or features) on which they are applied. Deep learning aims at discovering learning algorithms that can find multiple levels of representations directly from data, with higher levels representing more abstract concepts. In recent years, the field of deep learning has lead to groundbreaking performance in many applications such as computer vision, speech understanding, natural language processing, and computational biology.


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