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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
3,139 个评分
598 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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501 - 实用机器学习 的 525 个评论(共 588 个)

创建者 CHEN X

Dec 2, 2015

Feels like everything is solved using a caret package, while the back-end theory is only slightly touched. By using a single line command solver, student may lack the foundation for harder problems in the real world.

创建者 Daniel J R

Jan 17, 2019

Seems like a lot to pack into 4 -weeks. Should really be named introductory machine learning. Needs more depth and better development of the intuitions associated to each algorithm class to match the expectations.

创建者 Ayushmaan D V

Aug 16, 2020

The material covered was good and informative, the reference material was nice. But the video leactures themselves were lacking in many respects. The videos covered only a bare minimum and could have been longer.

创建者 Vinay K S

Feb 19, 2017

I like initial courses like Exploratory Data Analysis but later on it got harder to follow the lectures. A lot of topics were just rushed through and little effort was made to make them engaging or interesting.

创建者 Andrew W

Mar 13, 2018

Very interesting subject area, I think there is simply too much to cram into one course. Should consider spliting the subject into 2 courese or simply concentrate on only 1 or 2 main areas (e.g. cla

创建者 Andrew W

Feb 9, 2017

The videos are really tutorials on R functions for machine learning and data wrangling. A good substitute for "Machine Learning" by Andrew Ng in terms of managing data sets and exploratory analysis.

创建者 M. D

Jul 11, 2020

Content somewhat outdated. Referenced packages don't always work in current version of R. Material can be better explained with more detailed discussion of examples rather than theory.

创建者 Robert C

Aug 1, 2017

This course needs swirl assignments. I did fine on the quizzes and assignments, but I only feel like I learned a minimal amount of machine learning, even practical machine learning.

创建者 Raul M

Feb 12, 2019

The class is good but it is too simple. I expected the professor will provide more detail about the models. This is just an introduction and weak for a specialization.

创建者 Brian F

Aug 15, 2017

There was some good material in here, but it was rushed and is deserving of a much longer course - especially compared to some of the other modules in this course.

创建者 Chuxing C

Feb 5, 2016

the lack of assisted practices made it harder to digest the contents and methodologies.

strongly suggest to develop some practice problems with explanations.

创建者 Michalis F

May 26, 2017

Good in introducing caret package and getting some experience in running algorithms. Was expecting more in-depth discussion about the methods though.

创建者 Davin G

Aug 26, 2019

It's an excellent crash course to machine learning but the stats part was rushed. Had to look up external resources to understand what was going on.

创建者 Léa F

Jan 9, 2018

Rather good overview. The contents could dig deeper into each subject, and it would improve the course a lot if some exercises in Swirl were added.

创建者 Miguel J d S P

May 19, 2017

I didn't enjoy the supporting materials and the quizzes weren't very interesting. The final project was fine.

The subject is super interesting.

创建者 Max M

Dec 12, 2017

Should have gone into more depth and included swirl lessons, like previous courses. The quizzes were very challenging though, so that helped.

创建者 Kyle H

May 9, 2018

A brisk introduction to some of the basics of Machine Learning. Will leave with an understanding of a few ways to use the caret package.

创建者 Manuel E

Aug 8, 2019

Good course, but either explanations are too fast paced for the level of difficulty, or my neurons have began to decay with age.

创建者 Noelia O F

Jul 19, 2016

Good course for learning the basics of the caret package. However, it is not a good course for learning machine learning.

创建者 Joseph I

Feb 1, 2020

Material was very interesting but was covered at a very high level and a lot of additional learning was required.

创建者 José A G R

Feb 5, 2017

Superfluous but the existence of the package "caret" covers the gap of other libraries like "skilearn" of python

创建者 BAUYRJAN J

Mar 1, 2017

Instructor rushes the course and does not explain much in the same level of details as respective quiz requires

创建者 Hongzhi Z

Jan 2, 2018

All the formulas and code in slides are too abstract. If can be more charts to interpret that will be better.

创建者 Henrique C A

Oct 13, 2016

Exercises could be more complete, and some are outdated for latest R, giving slightly different results.

创建者 Alex F

Dec 29, 2018

A fine introduction, but there are much more engaging and better quality courses out there...