月深苍苔

机器视觉 模式识别 机器学习 数据挖掘 推荐算法。~~^^ ^^~~ 一卷道书三尺剑,半潭秋水一房山。

黑龙江 哈尔滨

感兴趣的主题: 数据结构 机器学习 摄影 笑话 文艺 数据挖掘 模式识别 机器视觉 80後

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Algorithms: Design and Analysis, Part 1 (Coursera) 5 个评论 关注

开始时间: 10/05/2015 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.

The Hardware/Software Interface (Coursera) 7 个评论 关注

开始时间: 06/30/2014 持续时间: 8 weeks

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

简介: Examines key computational abstraction levels below modern high-level languages. From Java/C to assembly programming, to basic processor and system organization.

Machine Learning (Coursera) 7 个评论 关注

开始时间: 待定 持续时间: Unknown

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

简介: Why write programs when the computer can instead learn them from data? In this class you will learn how to make this happen, from the simplest machine learning algorithms to quite sophisticated ones. Enjoy!

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.

Probability and Statistics (Khan Academy) 1 个评论 关注

开始时间: 随时 持续时间: 自主

主页: https://www.khanacademy.org/math/probability

简介: Introduction of the basics of Probability and Statistics

Introduction to Artificial Intelligence (Udacity) 2 个评论 关注

开始时间: 随时 持续时间: 自主

主页: https://www.udacity.com/course/cs271

简介: The objective of this class is to teach you modern AI. You will learn about the basic techniques and tricks of the trade. We also aspire to excite you about the field of AI.

Discrete Optimization (Coursera) 3 个评论 关注

开始时间: 03/04/2015 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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