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Natural Language Processing (CourseraArchive) 7 个评论 关注 开始时间: 04/22/2022 持续时间: 10 weeks 主页: https://www.coursera.org/course/nlangp 简介: Have you ever wondered how to build a system that automatically translates between languages? Or a system that can understand natural language instructions from a human? This class will cover the fundamentals of mathematical and computational models of language, and the application of these models to key problems in natural language processing. |
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Algorithms, Part I (CourseraArchive) 6 个评论 关注 开始时间: 04/22/2022 持续时间: 6 weeks 主页: https://www.coursera.org/course/algs4partI 简介: This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers basic iterable data types, sorting, and searching algorithms. |
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Algorithms, Part II (CourseraArchive) 5 个评论 关注 开始时间: 04/22/2022 持续时间: 6 weeks 主页: https://www.coursera.org/course/algs4partII 简介: This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. |
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Automata (CourseraArchive) 3 个评论 关注 开始时间: 04/22/2022 持续时间: 6 weeks 主页: https://www.coursera.org/course/automata 简介: This course covers finite automata, context-free grammars, Turing machines, undecidable problems, and intractable problems (NP-completeness). |
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Introduction to Recommender Systems (CourseraArchive) 3 个评论 关注 开始时间: 04/22/2022 持续时间: Unknown 主页: https://www.coursera.org/course/recsys 简介: This course introduces the concepts, applications, algorithms, programming, and design of recommender systems--software systems that recommend products or information, often based on extensive personalization. Learn how web merchants such as Amazon.com personalize product suggestions and how to apply the same techniques in your own systems! |
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StatLearning: Statistical Learning (Stanford Online) 3 个评论 关注 开始时间: 04/22/2022 持续时间: 未知 主页: https://class.stanford.edu/courses/HumanitiesScience/StatLearning/Winter2014/about 简介: This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical). |
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Introduction to Probability - The Science of Uncertainty (EdxArchive) 3 个评论 关注 开始时间: 04/22/2022 持续时间: 16 weeks 主页: https://www.edx.org/archive/introduction-probability-science-mitx-6-041x-0 简介: An introduction to probabilistic models, including random processes and the basic elements of statistical inference. |
