蒙在桥

广东 广州

感兴趣的主题: 计算机 社会网络分析 自然语言处理 数据挖掘 搜索引擎 机器学习

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Coding the Matrix: Linear Algebra through Computer Science Applications (CourseraArchive) 9 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/matrix

简介: Learn the concepts and methods of linear algebra, and how to use them to think about computational problems arising in computer science. Coursework includes building on the concepts to write small programs and run them on real data.

Introduction to Data Science (CourseraArchive) 5 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/datasci

简介: Join the data revolution. Companies are searching for data scientists. This specialized field demands multiple skills not easy to obtain through conventional curricula. Introduce yourself to the basics of data science and leave armed with practical experience extracting value from big data.

CVX101: Convex Optimization (Stanford Online) 1 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/Engineering/CVX101/Winter2014/about

简介: This course concentrates on recognizing and solving convex optimization problems that arise in applications. The syllabus includes: convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory, theorems of alternative, and applications; interior-point methods; applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance.

Linear and Integer Programming (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/linearprogramming

简介: This course will cover the very basic ideas in optimization. Topics include the basic theory and algorithms behind linear and integer linear programming along with some of the important applications. We will also explore the theory of convex polyhedra using linear programming.

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