Machine Learning (CourseraArchive) 29 个评论 关注

开始时间: 04/22/2022 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.

Neural Networks for Machine Learning (CourseraArchive) 5 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/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

开始时间: 04/22/2022 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!

Introduction to Artificial Intelligence (Udacity) 2 个评论 关注

开始时间: 04/22/2022 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.

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。]

加州理工学院公开课：机器学习与数据挖掘 (网易公开课) 0 个评论 关注

开始时间: 04/22/2022 持续时间: 加州理工学院公开课：机器学习与数据挖掘

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

简介: 这是涵盖机器学习基本理论、算法和应用的基础课程，结合理论和实践，生动介绍机器学习如何使运算系统得以根据获取的数据改善其表现，并将这些成果运用到工程、科技、金融商业等活动中。专业理论将包括线性模型、VC维、神经网络、支持向量机、数据探测法等。

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

开始时间: 04/22/2022 持续时间: 斯坦福大学公开课

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

简介: 人工智能的发展到已经进入了一个瓶颈期。近年来各个研究方向都没有太大的突破。真正意义上人工智能的实现目前还没有任何曙光。但是，机器学习无疑是最有希望实现这个目标的方向之一。斯坦福大学的“Stanford Engineering Everywhere ”免费提供学校里最受欢迎的工科课程，给全世界的学生和教育工作者。得益于这个项目，我们有机会和全世界站在同一个数量级的知识起跑线上。