LK不改名字了就算只有片刻我也不害怕。-Weibo北京 海淀区 感兴趣的主题: 不要乱贴标签1个粉丝 |
Introduction to Data Science (Udacity) 0 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/ud359 简介: This is one of the first courses we offer for students interested in the emerging field of data science.
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The Caltech-JPL Summer School on Big Data Analytics (CourseraArchive) 0 个评论 关注 开始时间: 04/22/2022 持续时间: 2 weeks 主页: https://www.coursera.org/course/bigdataschool 简介: This is an intensive, advanced summer school (in the sense used by scientists) in some of the methods of computational, data-intensive science. It covers a variety of topics from applied computer science and engineering, and statistics, and it requires a strong background in computing, statistics, and data-intensive research. |
db: Introduction to Databases (Stanford Online) 1 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/Engineering/db/2014_1/about 简介: "Introduction to Databases" was one of Stanford's inaugural three massive open online courses in the fall of 2011 and was offered again in early 2013. January 2014 will mark its third offering. The course includes video lectures and demos with in-video quizzes to check understanding, in-depth standalone quizzes, a wide variety of automatically-checked interactive programming exercises, midterm and final exams, a discussion forum, optional additional exercises with solutions, and pointers to readings and resources. Taught by Professor Jennifer Widom, the curriculum draws from Stanford's popular Introduction to Databases course. |
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). |
Python (Coursera专项课程) 5 个评论 关注 开始时间: 04/22/2022 持续时间: free 主页: http://www.codecademy.com/zh/tracks/python 简介: Learn the fundamentals of Python and dynamic programming. |
Computational Investing, Part I (CourseraArchive) 0 个评论 关注 开始时间: 04/22/2022 持续时间: Unknown 主页: https://www.coursera.org/course/compinvesting1 简介: Find out how modern electronic markets work, why stock prices change in the ways they do, and how computation can help our understanding of them. Build algorithms and visualizations to inform investing practice. |
Data Analysis and Statistical Inference (CourseraArchive) 1 个评论 关注 开始时间: 04/22/2022 持续时间: Unknown 主页: https://www.coursera.org/course/statistics 简介: This course introduces you to the discipline of statistics as a science of understanding and analyzing data. You will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena. |