Description
| Machine learning studies how to automatically learn from observed data to improve the performance of prediction, information extraction, clustering, pattern recognition, decision making, signal processing and even artificial intelligence. This course will introduce fundamental algorithms, theories and their practical applications. The content will cover (a) supervised learning, such as parametric and non-parametric algorithms, super vector machines and neural networks, (b) unsupervised learning, for example, data clustering, dimension reduction and deep learning and (c) practical applications on speech, image, audio signal and natural language processing or information retrieval and search, etc.
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