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実践的機械学習 に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による 実践的機械学習 の受講者のレビューおよびフィードバック

4.5
3,194件の評価
615件のレビュー

コースについて

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....

人気のレビュー

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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実践的機械学習: 601 - 606 / 606 レビュー

by Abhilash R N

2019年12月4日

This course is NOT for the beginner. Take time to finish all the beginner and foundation courses and then take time to learn R

by Yesica B

2021年12月29日

I wanna know, what is happening with my grade with this course. I still wait long time ago. Please, help me.

by Emily S A

2020年5月25日

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

by yi s

2016年7月19日

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

by Stephen E

2016年6月27日

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

by Stephane T

2016年1月31日

Too much surface, not enough depth.