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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
8,052 個評分

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

OA

2017年9月8日

This course is ideally designed for understanding, which tools you can use to do machine learning tasks in python. However, for deep understanding ML algorithms you should take more math based courses

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.

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1201 - Applied Machine Learning in Python 的 1225 個評論(共 1,464 個)

創建者 Mariano T

2020年5月18日

There are some problems with the assignments but the course is very good. You must improve the material for the assiggnment. I love the forum

創建者 Alireza M

2022年6月4日

Knowledgeable teacher but still need to improve some presentations to limit the need to get extra resources for understanding the materials

創建者 Srinivas R

2017年9月22日

Good overview of machine learning topics with practical exercises in the use of multiple techniques primarily through use of scikit-learn.

創建者 David W

2017年7月3日

Hands on and practical. Dr. CT and his staff have done a great job introducing Machine Learning. Where were you 20 years ago? Thank you!

創建者 Rakshit T

2018年7月10日

A good course for beginners in Machine Learning. You get to the learn the basics of many techniques and their implementation in python.

創建者 yannick t

2018年4月12日

Excellent lectures. However, I would have needed more guidance for the last assignment. I learned a lot, but through pain and struggle.

創建者 M V B

2020年10月9日

It was a great experience learning through Coursera ,who provides best faculty for making students understand easily.

thank you Cousera

創建者 GC

2021年3月31日

This course is useful, but the code is not updated, and the assignment and Module codes returned a lot of code deprecation warnings.

創建者 Prathmesh D

2020年7月15日

It was a great learning with you all got little problems but solved as per instructions and they helped me through that,thanking you

創建者 PRATIKKUMAR A P

2020年8月23日

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ience of machine learning using python. Very well explained algorithms and application through modules and assignments.

創建者 Muhammad I

2021年8月27日

Best Course if you are searching for the applied side of Machine learning and Assignment are very helpfull to make mucssle memory

創建者 MARCO S M H

2021年2月7日

excellent course, except for the last week. I think that the last part about decision trees, NN and randomforest could be better

創建者 Dr. P R K

2018年1月23日

Unlike the name suggests, this course only covers the Supervised learning side of the ML. However, the supervised side is good.

創建者 Michael S

2019年6月29日

Everybody has different skill levels, but this was really hard and really, really, really fast.

Did I say it was really fast?

創建者 New_diver N

2019年5月22日

Course content is very nice and covered aptly. I feel that some where more depth was necessary to understand the algorithms.

創建者 bob n

2020年8月31日

Tough, but fair weekly assessments. Lecturer is a bit on the dry, boring side. Be careful not to let you attention drift.

創建者 BHAGYASHREE B

2020年5月9日

Other than the subtle mistakes, the overall course was very informative. I wish there were more practise exercises though

創建者 Mohamed S

2020年3月26日

A comprehensive course by a wold class university,some teaching could have been better by using more interactive methods.

創建者 Amaira Z

2021年1月12日

Well explained course with good material in python, may be an additionnal week is needed for the unsupervised learning

創建者 Ekun K

2020年7月16日

This is a great course. I recommend using the Introduction to Machine Learning book to complement the lecture videos.

創建者 Wynona R N

2020年6月23日

Good introduction course on machine learning algorithms. The books and the readings are recommended to look through!

創建者 Amanda V

2018年6月2日

You will learn a lot. But the course is a little bit fast for regular students. Assignments deal with real problems.

創建者 Rohith S

2017年11月16日

A few more code examples would have helped better understand various packages provided by Python and how to use them

創建者 lcy9086

2019年2月2日

Great course on doing machine learning use sklearn and put little but enough explanation of the theories behind it!

創建者 Alexandr S

2019年2月24日

It would be nice to have more practical assignments like the last one! Anyway it was very interesting! Thank you!