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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
7,520 個評分
1,371 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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1326 - Applied Machine Learning in Python 的 1350 個評論(共 1,354 個)

創建者 José D A M

2020年6月21日

Too fast, yet too difficult. Needs deeper explanation.

創建者 Navoneel C

2017年11月21日

Nice and Informative but not practically effective

創建者 Priyanka v

2020年5月8日

if it is more detailedthen it will be more useful

創建者 Sameed K

2018年3月15日

have to figure out a lot of things on you own.

創建者 Andy S

2019年6月4日

It could have been better with more examples.

創建者 Shan J

2020年4月12日

The explanation could have been much better.

創建者 Sagar J

2021年3月21日

Good start but i was very boring later on.

創建者 Jeremy D

2017年7月10日

The topics were good, but too many were d

創建者 Ryan S

2017年12月12日

Homeworks are inconvenient to submit

創建者 PIYUSH A

2020年5月16日

The narration was a bit boring.

創建者 shreyas

2020年6月29日

Teacher wasn't very good

創建者 Abir H R

2020年6月30日

very long videos

創建者 Wojciech G

2017年10月28日

To fast paced.

創建者 Aarya P

2020年9月30日

Really disappointed with the course ...you may ask why??

The first thing is the instructor , super boring. The instructor (with all due respect) was very dry and the lectures were super uninteresting. When he keeps on talking code, but doesn't really explain stuff. The material and lectures were dry and colorless.

Me without having good statistics background had huge difficulties understanding the concepts. Please i recommend everyone to have good knowledge in statistics before starting the course. ABSOLUTELY NOT THE BEGINNER LEVEL AND NEITHER INTERMIDIATE LEVEL .the course is quiteeeee difficult.

You also need to have a lot of self study , which i am not a big fan of. I hope they make the course more fun rather than a man constantly talking on the screen .

創建者 Daniel J

2021年4月30日

I found this course quite challenging to complete. The assignments are difficult (which is good, they are practical and I enjoyed them) and only a fraction of things is explained in the videos. I really found much better learning materials around the web (and for free!). For applied machine learning course, I would expect more practical videos. Also the process of submitting assignments is really frustrating, I spent half the time correcting errors that were not related to the assignment objective. If this course was not part of specialization, I would not complete it.

創建者 Douglas H

2021年4月10日

Lectures are good but they expect you to extract too many fine details from them in order to pass the quizzes and assignments. You'd have to watch these oral lessons ten times in order to pass the tests, which are needlessly nitpicky.

創建者 Oswaldo C

2020年8月22日

Los videos no son suficientemente extensos ni para explicar el código, ni para explicar la teoría detrás de los algoritmos, se queda a medio camino de los dos siendo insuficiente en ambos casos

創建者 Jean-Michel P

2021年6月2日

The better course of this stack... and that's all the positive feedback I have. This course is still very poorly designed and unstructured with a bunch of unfixed mistakes after 4+ years.

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 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 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.