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學生對 约翰霍普金斯大学 提供的 实用机器学习 的評價和反饋

4.5
3,054 個評分
579 條評論

課程概述

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
2020年8月13日

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
2017年2月28日

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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376 - 实用机器学习 的 400 個評論(共 570 個)

創建者 Paul K

2017年4月8日

Very good summary of strengths/weaknesses of various machine learning algorithms. This lecturer's style and production quality is much higher than in the previous two courses in the specialization series.

創建者 Erika G

2016年7月28日

I learned a lot in this class. There are slight gaps from the depth of material covered in the lectures to the quizzes and assignment. If you're good at researching online, you'll be fine.

創建者 Jiarui Q

2019年3月27日

It is still kind of hard for a learner to understand the methods. But it gives me a overall introduction of machine learning and I will have further learning in the future.

創建者 Matthew C

2017年12月11日

Lots of good material, but some things (like PCA) didn't receive enough coverage in the lectures. The quizzes also weren't great at testing the material in the lectures.

創建者 Utkarsh Y

2016年11月17日

Great course. Only missing piece is the working information / maths behind the models. But as the name suggests it teaches practical approach towards machine learning.

創建者 Craig S

2018年2月12日

Not as detailed as some others in the specialization which is a shame but good none the less. The videos go through the info quickly so be prepared to go back over.

創建者 Roberto G

2017年5月20日

Great as an introduction for someone with no practical experience. Lectures are too theoretical and lack some examples to translates the theory into practice

創建者 Nicholas T

2020年7月3日

Very good course. Fast paced and a lot of self study required to fully understand some of the nuances of the R (if you're not familiar with the language).

創建者 Eric L

2016年6月2日

Great course, very high paced with a lot of information. would have been great to add two more weeks and another project to use more machine learning

創建者 Igor H

2016年9月10日

Rather basic, nevertheless a good introduction to the topic of machine learning with R. Mostly concentrated on applications of the R caret package.

創建者 Lee G

2017年9月22日

A very good starter course on Machine Learning in R with great links to various resources that students and delve deeper into the various topics.

創建者 Yashaswi P

2020年5月24日

Good Course the covers a lot of practical aspects and relevant to the real world solution.

Good References and Learning Materails are available

創建者 Ann B

2017年9月6日

Good class to get the basics of Practical Machine Learning. This course is best taken as a part of the data science series from John Hopkins.

創建者 Hernan S

2016年12月13日

The quiz should be constructed in a way that depends less on the version of the libraries used. The rest of course was excellent.

創建者 Jakub W

2018年9月24日

Vary practical approach, almost no theory or in-depth explanation of the subject, but a lot of focus on applying ML in practice

創建者 Md F A

2017年8月14日

To me with this course, the best learning aspect is the final project; how to use Machine Learning Algorithms on data analysis.

創建者 Rhys T

2017年10月10日

Good course, some aspects of the assignment were a bit beyond the scope of what the course teaches but overall I learnt a lot.

創建者 Níck F

2016年9月27日

Was pretty good, but quite short and some assignments did not align as well with the lecture material as they could have.

創建者 Michael O D

2020年1月10日

This is a great course, but it would be good to see it updated to use the newer evolution of the caret package, parsnip.

創建者 Tongesai K

2016年2月8日

Very good course. I am very knew to this topic but am sure will find a lot of application in my speciality - geophysics

創建者 Kevin S

2016年3月2日

Good introduction to machine learning, might suffer a bit from trying to cover too much ground in such a short time.

創建者 Sulan L

2018年11月19日

I hope we can have more détails in this cours and to see how to use the algorithms for the big data. Thank you.

創建者 A. R C

2017年10月20日

I enjoyed it but it needs indeed to deep into many concepts, which are just briefly named during the course.

創建者 marcelo G

2016年8月14日

Great course, very demanding, but it could use more reading material, ebooks instead of links on video.

創建者 Jeffrey E T

2016年3月28日

Good overview of available techniques and the Caret package. Will get you started in machine learning.