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."

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!

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。]

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

开始时间: 04/22/2022 持续时间: 未知

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

简介: This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines. Some unsupervised learning methods are discussed: principal components and clustering (k-means and hierarchical).