邱枫的围脖

武汉技术宅爱皇马爱利物浦爱#说人话#

湖北 武汉

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English Composition I: Achieving Expertise (Coursera) 1 个评论 关注

开始时间: 09/22/2014 持续时间: 12 weeks

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

简介: You will gain a foundation for college-level writing valuable for nearly any field. Students will learn how to read carefully, write effective arguments, understand the writing process, engage with others' ideas, cite accurately, and craft powerful prose. We will create a workshop environment.

Introduction to Probability - The Science of Uncertainty (edX) 3 个评论 关注

开始时间: 待定 持续时间: 16 weeks

主页: https://www.edx.org/course/introduction-probability-science-mitx-6-041x-0

简介: An introduction to probabilistic models, including random processes and the basic elements of statistical inference.

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.

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).

Critical Thinking in Global Challenges (Coursera) 1 个评论 关注

开始时间: 待定 持续时间: Unknown

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

简介: In this course you will develop and enhance your ability to think critically, assess information and develop reasoned arguments in the context of the global challenges facing society today.

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。]

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