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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
7,860 個評分
1,430 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

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!!

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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676 - Applied Machine Learning in Python 的 700 個評論(共 1,415 個)

創建者 Juan S

2020年2月2日

Good overview to a lot of different ML techniques

創建者 Dongquan S

2019年10月9日

Very well designed course. Learned a lot. Thanks!

創建者 Kee K Y

2021年8月8日

Practical and excellent course for ML Specialist

創建者 Arturo R

2021年7月15日

Very well balanced between dificuty and learning

創建者 Manan S

2020年5月25日

Awesome Teaching and Assignemts are very usefull

創建者 DEBAYAN M

2019年6月4日

A must -learn for every aspiring data scientist.

創建者 Mischa L

2018年1月6日

Great course with excellent homework assignments

創建者 Shivani R

2020年7月19日

Very good course. Detailed videos & explanation

創建者 SRIHARI

2017年7月18日

This is good course gives in depth information.

創建者 M.Fauzan A

2021年1月1日

thanks for knowledge and live to inspire,peace

創建者 Ana K A d M

2020年2月7日

Excellent balance between theory and practice!

創建者 Krishna P S

2018年3月1日

Excellent course. Nicely designed & delivered.

創建者 Eray Ö

2017年9月26日

great course with a lot of hands-on experience

創建者 Mohammad Q M A

2020年7月13日

It is A great course ! I recommend to take it

創建者 Punam P

2020年4月15日

Very Nice Course..I really Enjoyed it..Thanks

創建者 Yongqing H

2019年8月5日

It's so hard. But every endless trying worth.

創建者 Dario M

2019年7月12日

So far the best course in this specialization

創建者 Rohit M S

2019年3月22日

The Course is amazing. you get to learn a lot

創建者 Xiaoyue Z

2018年7月30日

A very helpful and confidence-building class!

創建者 Ruyang L

2018年4月20日

Very interesting course, enjoyed it very much

創建者 zios s

2017年11月23日

great course very useful in data science job.

創建者 Om P

2020年5月17日

perfect for beginners! thank you, professor!

創建者 Pilar V

2019年9月14日

Super interesting course and specialization!

創建者 Joan P

2017年11月5日

Very interesting last programming assignment

創建者 David M

2017年7月7日

Great introduction to Scikit-learn tool set.