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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
7,977 個評分
1,452 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!!

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

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726 - Applied Machine Learning in Python 的 750 個評論(共 1,442 個)

創建者 Jay G

2020年3月20日

Thank you so much for this amazing course

創建者 Yang L

2019年11月28日

love the final assignment. Had great fun!

創建者 Gustavo H d N

2019年8月31日

Good balance between theory and practice.

創建者 dan s

2017年12月30日

Fantastic Course. I highly recommend it.

創建者 Tinniam V G

2017年9月7日

Terrific course. Many thanks to the Prof!

創建者 Nguyen T S

2021年11月16日

T​hank you! this course is very helpful.

創建者 Vaneeza I

2021年8月29日

Highly recommended courses for beginners

創建者 William H

2019年9月2日

Excellent instructor and course material

創建者 Patrick K

2018年11月22日

Very nicely explained. Highly recommend.

創建者 József V

2018年4月29日

Broad range of ML knowledges is covered!

創建者 hema m M

2020年6月30日

Very helpful and interesting resources.

創建者 Vishant J

2020年4月18日

excellent course for beginners as well!

創建者 Alexander G

2019年7月15日

Nice course on machine learning basics!

創建者 Nan L

2018年6月17日

I think this course is difficult for me

創建者 Ranjeetha V

2022年5月16日

E​xcellent teacher and well explained!

創建者 Henrique G A

2021年1月25日

Best course with the best professor!!!

創建者 Pavan M

2021年1月19日

Course is Good and Very well presented

創建者 Muhammad E

2020年10月26日

very good course totally recommend it

創建者 RAMISETTI B R

2020年2月7日

wow!!!great feeling from learning here

創建者 Mariano S C

2019年10月25日

great course, excellent teaching staff

創建者 Shadi A

2019年5月6日

Best Instructor and simple explanation

創建者 Nilesh I

2018年10月5日

Practical, I liked the evaluation part

創建者 SANKURU M K

2020年5月17日

very nice course.usefull for beginers

創建者 Marion T

2019年5月31日

good introduction to machine learning

創建者 Michael T

2019年2月21日

Great content and reference materials