孙小琦爱下雪

北京 海淀区

感兴趣的主题: 独立 开心

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Machine Learning (CourseraArchive) 29 个评论 关注

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.

Neural Networks for Machine Learning (CourseraArchive) 5 个评论 关注

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

简介: Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well.

Machine Learning (CourseraArchive) 7 个评论 关注

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!

Introduction to Artificial Intelligence (Udacity) 2 个评论 关注

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.

Artificial Intelligence (EdxArchive) 6 个评论 关注

主页: https://www.edx.org/archive/artificial-intelligence-uc-berkeleyx-cs188-1x

简介: UC Berkeley's upper division course CS188: Introduction to Artificial Intelligence now available to everyone online.
 
"Nothing short of awesome. This is a top-notch class that teaches you a lot of important concepts in optimization and AI, while making you feel like you're on a wonderful adventure of discovery and fun." edX student review

機器學習基石 (Machine Learning Foundations) (CourseraArchive) 10 个评论 关注

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。]

StatLearning: Statistical Learning (Stanford Online) 3 个评论 关注

主页: https://class.stanford.edu/courses/HumanitiesScience/StatLearning/Winter2014/about

简介:

斯坦福大学公开课 :机器学习课程 (网易公开课) 0 个评论 关注

主页: http://v.163.com/special/opencourse/machinelearning.html

简介:

Probabilistic Graphical Models (CourseraArchive) 5 个评论 关注

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.

机器学习 (EdxArchive) 0 个评论 关注

主页: http://video.chaoxing.com/serie_400004125.shtml

简介: None

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