李元甲

Follow Excellence. Success will chase you.

上海 松江区

感兴趣的主题: NLP ML DM 对话系统

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李元甲 的课程评论

李元甲 评论了课程: Python

2013-12-29 17:56

大约有三百个左右的小练习,内容比较基础简单,适合python入门学习。

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李元甲 关注的课程

Python (Codecademy) 5 个评论 关注

开始时间: 随时 持续时间: free

主页: http://www.codecademy.com/zh/tracks/python

简介: Learn the fundamentals of Python and dynamic programming.

Machine Learning (Coursera) 28 个评论 关注

开始时间: 待定 持续时间: Unknown

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

简介: Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Introduction to Statistics (Udacity) 3 个评论 关注

开始时间: 随时 持续时间: 自主

主页: https://www.udacity.com/course/st101

简介: Statistics is about extracting meaning from data. In this class, we will introduce techniques for visualizing relationships in data and systematic techniques for understanding the relationships using mathematics.

计算广告学 (师徒网) 5 个评论 关注

开始时间: 12/15/2012 持续时间: 8 weeks

主页: http://study.163.com/course/courseMain.htm?courseId=321007

简介: 本课程从计算广告各个阶段所遇到的市场挑战为出发点,清晰解释了广告市场纷繁复杂的产品逻辑,并且对其中的关键技术和算法做了深入的探讨。依次介绍了合约广告系统(Agreement-based Advertising),竞价广告系统(Auction-based Advertising),广告交易市场(Ad Exchange)等重要课题。

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.

Natural Language Processing (Coursera) 7 个评论 关注

开始时间: 02/24/2013 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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