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

开始时间: 09/08/2015 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。]

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.

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

开始时间: 待定 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.

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

开始时间: 01/20/2014 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).

Probabilistic Graphical Models (Coursera) 5 个评论 关注

开始时间: 04/08/2013 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.

Mathematical Methods for Quantitative Finance (Coursera) 2 个评论 关注

开始时间: 06/01/2015 持续时间: 8 weeks

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

简介: Mathematical Methods for Quantitative Finance covers topics from calculus and linear algebra that are fundamental for the study of mathematical finance. Students successfully completing this course will be mathematically well prepared to study quantitative finance at the graduate level.

Introduction to Bootstrap – A Tutorial (edX) 0 个评论 关注

开始时间: 待定 持续时间: 3 weeks

主页: https://www.edx.org/course/introduction-bootstrap-tutorial-microsoft-dev203x-0

简介: Learn how to use Bootstrap to implement mobile first web pages with CSS and JavaScript.