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學生對 密歇根大学 提供的 Applied Machine Learning in Python 的評價和反饋

4.6
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7,754 個評分
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1,416 條評論

課程概述

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. The issue of dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled. Supervised approaches for creating predictive models will be described, and learners will be able to apply the scikit learn predictive modelling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting). The course will end with a look at more advanced techniques, such as building ensembles, and practical limitations of predictive models. By the end of this course, students will be able to identify the difference between a supervised (classification) and unsupervised (clustering) technique, identify which technique they need to apply for a particular dataset and need, engineer features to meet that need, and write python code to carry out an analysis. This course should be taken after Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation in Python and before Applied Text Mining in Python and Applied Social Analysis in Python....

熱門審閱

AS
2020年11月26日

great experience and learning lots of technique to apply on real world data, and get important and insightful information from raw data. motivated to proceed further in this domain and course as well.

FL
2017年10月13日

Very well structured course, and very interesting too! Has made me want to pursue a career in machine learning. I originally just wanted to learn to program, without true goal, now I have one thanks!!

篩選依據：

651 - Applied Machine Learning in Python 的 675 個評論（共 1,400 個）

創建者 Archunan G

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2019年12月3日

Course is interesting and nice . quiz made well .

創建者 MAINAK C

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2019年8月20日

very nice and apt course for all types of learners.

創建者 Lutz H

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2019年6月17日

Really well explained. Great excersices! Well done!

創建者 AMAN K

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2019年3月6日

Course Material is quite interesting and practical.

創建者 Mai N

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2018年9月8日

Good starting points for any machine learning folks

創建者 Ebenezer A W

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2017年11月14日

A really nice course to begin machine learning with

創建者 LEE D D

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2017年11月9日

Perfect and hard course than Andrew Ng's ML course!

創建者 Artur A

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2017年8月4日

Best introduction to sklearn library I came across!

創建者 zhang y

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2021年10月3日

comprehensive machine learning course for beginner

創建者 Pratama A A

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2020年7月14日

If you're beginner i suggest dont take this course

創建者 Ameya B

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2020年7月3日

Overall good intro to actually using scikit-learn.

創建者 likejian

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2020年5月14日

It’s very nice course to learn ML for the new guys

創建者 Abdelrahman M s A

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2018年2月26日

One of the best practical ML courses in the field!

創建者 Arun S

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2017年11月9日

Great professor with lot of real world experience.

創建者 ChanLung

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2017年7月31日

Excellent Machine Learning Course for application!

創建者 Rui J

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2021年11月16日

it is so much fun to write programms on your own!

創建者 Melnikova O

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2020年12月7日

I like this cource. It gives a very good overview

創建者 Bauyrzhan A

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2020年11月15日

It is decent course with fair level of complexity

創建者 Anuj P

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2020年6月20日

tremendous knowledge for applied machine learning

創建者 SUBBA R D

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2020年6月11日

Very useful course especially for the beginners .

創建者 Raul V

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2020年4月17日

Very well organized and challenging real datasets

創建者 Prachi A

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2020年3月1日

Amazing course for a beginner in Machine Learning

創建者 Juan S

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2020年2月2日

Good overview to a lot of different ML techniques

創建者 Dongquan S

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2019年10月9日

Very well designed course. Learned a lot. Thanks!

創建者 Kee K Y

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2021年8月8日

Practical and excellent course for ML Specialist

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