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学生对 约翰霍普金斯大学 提供的 实用机器学习 的评价和反馈

4.5
3,106 个评分
588 条评论

课程概述

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation....

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MR
Aug 13, 2020

recommended for all the 21st centuary students who might be intrested to play with data in future or some kind of work related to make predictions systemically must have good knowledge of this course

AD
Feb 28, 2017

Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.

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576 - 实用机器学习 的 579 个评论(共 579 个)

创建者 Emily S A

May 25, 2020

In my opiion, this course needs to be improved a lot. There are almost nothing Practical Machine Learning.

创建者 yi s

Jul 19, 2016

too general no depth, not recommended for science or engineering degree holders

创建者 Stephen E

Jun 27, 2016

To be honest I don't think this is worth the money.

创建者 Stephane T

Jan 31, 2016

Too much surface, not enough depth.