zhlqqz

山东 济宁

感兴趣的主题: IT数码 人工智能 编程 算法 DOTA

1个粉丝

zhlqqz 的课程评论

更多评论

zhlqqz 关注的课程

A Brief History of Humankind (Coursera) 3 个评论 关注

开始时间: 待定 持续时间: Unknown

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

简介: The course surveys the entire length of human history, from the evolution of various human species in the Stone Age up to the political and technological revolutions of the twenty-first century.

Algorithms, Part I (Coursera) 6 个评论 关注

开始时间: 01/22/2016 持续时间: 6 weeks

主页: https://www.coursera.org/course/algs4partI

简介: This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers basic iterable data types, sorting, and searching algorithms.

Algorithms, Part II (Coursera) 5 个评论 关注

开始时间: 03/16/2016 持续时间: 6 weeks

主页: https://www.coursera.org/course/algs4partII

简介: This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations.

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).

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.

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。]

Algorithms: Design and Analysis, Part 1 (Coursera) 5 个评论 关注

开始时间: 10/05/2015 持续时间: 6 weeks

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

简介: In this course you will learn several fundamental principles of algorithm design: divide-and-conquer methods, graph algorithms, practical data structures (heaps, hash tables, search trees), randomized algorithms, and more.

更多课程