freealbert

Blog : dym.me

江苏 南京

感兴趣的主题: Linux 军事 latex

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freealbert 的课程评论

freealbert 评论了课程: 中國古代歷史與人物--秦始皇

2013-11-01 00:13

历史之于我,意义在于鉴前人之荣辱得失以自省。秦这一族由弱而强再走向族灭, 就如同一个屌丝逆袭后得意忘形自我毁灭, 让人敬佩同时也扼腕叹息。当然, 如果只是传达史实, 那这门课就跟普通的百家讲坛没啥区别的, 这门课的精髓就在于老师一直强调的思辨。很期待他的下一门课——史记。

freealbert 评论了课程: Image and video processing: From Mars to Hollywood with a stop at the hospital

2013-10-31 20:55

这门课定位应该是图像处理的入门课程, 内容很全面也很鲜活,从灰度,像素等的最基础的知识一直讲到如今在学术界大红大紫的稀疏表示。Slide和Demo演示都很赞,相信应该能激起很多人对图像处理的兴趣,K-SVD算法就是在他的课上搞明白的。 关于授课老师, Sapiro本人是图像处理的大牛, 光在IEEE上就有文章150余篇, 在PDE和小波方面都有很大的贡献.

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freealbert 关注的课程

Image and video processing: From Mars to Hollywood with a stop at the hospital (Coursera) 1 个评论 关注

开始时间: 01/04/2016 持续时间: 9 weeks

主页: https://www.coursera.org/course/images

简介: In this class you will look behind the scenes of image and video processing, from the basic and classical tools to the most modern and advanced algorithms.

中國古代歷史與人物--秦始皇 (Coursera) 6 个评论 关注

开始时间: 05/27/2015 持续时间: 9 weeks

主页: https://www.coursera.org/course/chinesehistory

简介: 這是一門透過全新方式設計的歷史入門課,目的在於使非文史專業的學生重新發現學習歷史的樂趣,並重新認識學習歷史的價值。

Analytic Combinatorics (Coursera) 0 个评论 关注

开始时间: 11/06/2015 持续时间: 6 weeks

主页: https://www.coursera.org/course/ac

简介: Analytic Combinatorics teaches a calculus that enables precise quantitative predictions of large combinatorial structures. This course introduces the symbolic method to derive functional relations among ordinary, exponential, and multivariate generating functions, and methods in complex analysis for deriving accurate asymptotics from the GF equations.

Probabilistic Graphical Models (Coursera) 5 个评论 关注

开始时间: 04/08/2013 持续时间: 11 weeks

主页: https://www.coursera.org/course/pgm

简介: In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.

CVX101: Convex Optimization (Stanford Online) 1 个评论 关注

开始时间: 01/20/2014 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.

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