北方的冬雪 评论了课程: Machine Learning

2013-09-30 10:27

呵呵，很多同学说Andrew Ng老师的ML课程代码给的太全，有些失望~
别忘这是机器学习入门课程，掌握ML基础即时和培养思维方式，带你走进ML世界是最重要的，不是一门课程~

Probabilistic Graphical Models (CourseraArchive) 5 个评论 关注

开始时间: 04/22/2022 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.

Natural Language Processing (CourseraArchive) 7 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/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.

Learning From Data (EdxArchive) 1 个评论 关注

开始时间: 04/22/2022 持续时间: 10 weeks

主页: https://www.edx.org/archive/learning-data-caltechx-cs1156x

简介: Introductory Machine Learning course covering theory, algorithms and applications. Our focus is on real understanding, not just "knowing."

Introduction to Recommender Systems (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/recsys

简介: This course introduces the concepts, applications, algorithms, programming, and design of recommender systems--software systems that recommend products or information, often based on extensive personalization. Learn how web merchants such as Amazon.com personalize product suggestions and how to apply the same techniques in your own systems!

機器學習基石 (Machine Learning Foundations) (CourseraArchive) 10 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/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。]