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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
8,058 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

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:

1451 - Applied Machine Learning in Python 的 1465 個評論(共 1,465 個)

創建者 Vjaceslavs M

2021年4月4日

This course is outdated by few years and not been updated in general with lots of mistakes in assignments and on slides making it very not ejoyable to use.

創建者 David C

2020年11月8日

Not as good as prev. courses. Univ. of mic. should update or get ride of this module

創建者 Gallina S

2021年11月19日

G​ood curriculumn, nice assignments. Very poorly presented by the professor!!!

創建者 Paul C

2021年3月27日

Frankly the quiz questions are ridiculous and no explanation is given why answers are considered incorrect. The wording of the answers is not clear and any from 5 is 120 permutations. You get three attempts and then you have to wait 8 hours. Not great if you are studying part-time. I gave a star for the quality of the video which seemed good although I already know the theory from my university course. However, there was no written material - which again helps answer the questions. This is only a coursera courses, tests should be there to help learning not hinder it.

創建者 Dhawal M

2022年1月13日

There is no value addition after listening to the video lectures. You might as well just read the suggested Resources and attempt the Assignments on your own. I have never attended college and might assume that all college lectures are drab and monotonous.

創建者 Michael O S

2021年9月16日

There's a bug in the final homework that the TA and peers don't sufficiently explain how to solve so I can't get the course certificate just by knowing the content taught in the course. It's not fair.

創建者 Topiltzin H

2021年3月22日

Course was not as expected, I think XG Boost for instance is quite large and was covered in less than 20 minutes.

創建者 SAMADRITO B

2021年3月19日

The course is full of faulty assignment grader and the concepts given are not up to the mark

創建者 Aditya M

2020年7月17日

Can't the lecturer use proper slides with proper diagrams for a better explanation.

創建者 Deyner L P

2022年5月29日

Demasiados errores a la hora de enviar los laboratorios.

創建者 SHREYAS D

2020年8月14日

Things in the beginning are not explained properly

創建者 Joe R

2021年3月31日

Terrible lectures - assignments were good though

創建者 Varun D

2022年7月19日

A lot of the course has much to improve.

創建者 Konark Y

2020年5月10日

many issues while submitting assignments

創建者 Oleg G

2020年5月16日

enrolled by mistake want to u nenroll