张姆克鲁斯

40万字长篇言情小说《东京的那些人那些事》创作中

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感兴趣的主题: 大型动物 monicazfaye NOSQL ATHandAKG 森林幼儿园 宏观经济

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张姆克鲁斯 关注的课程

High Performance Scientific Computing (Coursera) 1 个评论 关注

开始时间: 02/20/2015 持续时间: 10 weeks

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

简介: Programming-oriented course on effectively using modern computers to solve scientific computing problems arising in the physical/engineering sciences and other fields. Provides an introduction to efficient serial and parallel computing using Fortran 90, OpenMP, MPI, and Python, and software development tools such as version control, Makefiles, and debugging.

Introduction to Data Science (Coursera) 5 个评论 关注

开始时间: 06/30/2014 持续时间: 8 weeks

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

简介: Join the data revolution. Companies are searching for data scientists. This specialized field demands multiple skills not easy to obtain through conventional curricula. Introduce yourself to the basics of data science and leave armed with practical experience extracting value from big data.

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.

Financial Markets (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/financialmarkets

简介: An overview of the ideas, methods, and institutions that permit human society to manage risks and foster enterprise.

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).

Mining Massive Datasets (Coursera) 1 个评论 关注

开始时间: 09/12/2015 持续时间: 7 weeks

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

简介: This class teaches algorithms for extracting models and other information from very large amounts of data. The emphasis is on techniques that are efficient and that scale well.

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