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Calculus: Single Variable (CourseraArchive) 4 个评论 关注 开始时间: 04/22/2022 持续时间: Unknown 主页: https://www.coursera.org/course/calcsing 简介: This course provides a brisk, entertaining treatment of differential and integral calculus, with an emphasis on conceptual understanding and applications to the engineering, physical, and social sciences. |
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Algebra I (MIT公开课) 1 个评论 关注 开始时间: 04/22/2022 持续时间: 未知 主页: http://ocw.mit.edu/courses/mathematics/18-701-algebra-i-fall-2010 简介: This undergraduate level Algebra I course covers groups, vector spaces, linear transformations, symmetry groups, bilinear forms, and linear groups. |
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Discrete Optimization (CourseraArchive) 3 个评论 关注 开始时间: 04/22/2022 持续时间: 9 weeks 主页: https://www.coursera.org/course/optimization 简介: Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization, including constraint programming, local search, and mixed-integer programming. |
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機器學習基石 (Machine Learning Foundations) (CourseraArchive) 10 个评论 关注 开始时间: 04/22/2022 持续时间: 8 weeks 主页: https://www.coursera.org/course/ntumlone 简介: Machine learning is the study that allows computers to adaptively improve their performance with experience accumulated from the data observed. The course teaches the most fundamental algorithmic, theoretical and practical tools that any user of machine learning needs to know. [機器學習旨在讓電腦能由資料中累積的經驗來自我進步。本課程將介紹各領域中的機器學習使用者都應該知道的基礎演算法、理論及實務工具。] |
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機器學習技法 (Machine Learning Techniques) (CourseraArchive) 2 个评论 关注 开始时间: 04/22/2022 持续时间: 8 weeks 主页: https://www.coursera.org/course/ntumltwo 简介: The course extends the fundamental tools in "Machine Learning Foundations" to powerful and practical models by three directions, which includes embedding numerous features, combining predictive features, and distilling hidden features. [這門課將先前「機器學習基石」課程中所學的基礎工具往三個方向延伸為強大而實用的工具。這三個方向包括嵌入大量的特徵、融合預測性的特徵、與萃取潛藏的特徵。] |
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Algorithms: Design and Analysis, Part 1 (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/algo 简介: In this course you will learn several fundamental principles of algorithm design: divide-and-conquer methods, graph algorithms, practical data structures (heaps, hash tables, search trees), randomized algorithms, and more. |
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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. |
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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. |
