This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain-computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks.
Collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms, hosted by the UC Irvine.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Collections of speech and text databases, lexicons, and other resources for linguistics research and development purposes, some free. KSL has access to several fee-based collections.
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