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Bewertung und Feedback des Lernenden für Applied Machine Learning in Python von University of Michigan

4.6
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8,251 Bewertungen

Über den Kurs

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....

Top-Bewertungen

OA

8. Sep. 2017

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

13. Okt. 2017

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!!

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1201 - 1225 von 1,499 Bewertungen für Applied Machine Learning in Python

von Julien Z

6. Mai 2020

Very good mix of video and python notebook. Some improvement can be done with the AutoGrader like get back the error python stack trace.

Globally, very good course - strongly recommanded

von Kai K

4. Juni 2018

The final assignment passing was a little too east,

there not being need to use fully what I learnt.

Still,the overall course was very good, and I am willing to keep on take other courses.

von Vinicius d A O

16. März 2020

This course was very good, with a lot of information and important tips for me. The instructor is good but he is long winded, so this course was very long with videos during 20 minutes.

von Saman H A

15. Aug. 2019

- more technical materials, comparisons and better classified details should've been provided, especially to be more proportional to the assignments.

-again, subtitles were full of typos

von Ashrulochan S

5. Mai 2022

Outstanding course content and curriculum for intermediate learners. Learnt some basic applications of machine learning in detail. Enjoyed while working on assignments and graded quiz.

von philippe p

7. Juni 2017

The course is well balanced but the progression becomes quite agressive at Week3 and culminate at Week4 with a real life case assignment without much guidance. Great experience dough.

von Vaishnavi M

29. Juni 2020

Amazingly explained. An intermediate Machine Learner would definitely get clarity of concepts already learned and also new concepts explained so skillfully with graphs and diagrams.

von Alex E

27. Aug. 2018

Good overview of methods in ML. Would have been nice if the lectures contained a little more mathematical rigor and explanation of why and how the various algorithms are effective.

von Virgil C L

13. Feb. 2018

Good course and prof.

The exam and exercise in very interesting according to what I learn in following all videos, with this i improved my level in python progamming, I recommended.

von Eugene S

3. Juli 2017

Automatic assignment grader has room for improvement. Some python code that works perfectly well when run locally or on the course web page would crash when run by autograder.

von Jiunjiun M

7. März 2018

The class material is well prepared and make machine learning very easy to learn. The first three homework assignment is a bit hand-holding but the last one is really good.

von Abrar A

27. Aug. 2022

The course material is very good and the explanation is excellent. It can be improved much more if the python and used libraries are updated to more current versions.

von Amine D

22. Okt. 2019

Good Course, i would have liked a little bit more theory about the algorithms, but this is an applied course of ML. Projects are good and the readings are interessting!

von Gautam P

20. Nov. 2017

Videos are good and had challenging assignments. I enjoyed learning new concepts. I wish we had one more week to practice more on advanced Machine learning concepts.

von Giovanni S

16. Juni 2020

Very interesting, a lot of focus of statistica theory and little less (as compared to previous courses of specialization) on practical examples and implementation.

von Jiangzhou F

23. Juni 2020

Good overall but some concepts and python functions need more explanations. Maybe 5 or 6 weeks are more appropriate for this course. It is too dense under 4 week.

von Holden L

31. Aug. 2019

better than the first two courses of this specialization for the content is coherent and the assignment is relevant to the knowledge taught in the course video.

von Leon V

2. Juli 2017

Request: Can we have the instructions with a "translation" to "regular" English - for those of us who still have to get used to machine learning jargon? Thanks.

von Christian P

5. Aug. 2019

Code and examples were very useful. Teaching a bit lengthy and detailed at times. Overall a very good course for getting hands-on machine learning in python.

von Weiqi Y

24. Okt. 2017

It's alright as a course focusing on applied techniques. If you are expecting more theories and understanding of the algorithms, this one may not for you

von Miguel A N P

13. März 2022

Vary good course, vey well explained, the only problem I used to have was about the assignments, there were some ptechnical problems with the files

von Sidharth R

9. Mai 2021

the authors can include more coding questions so as to not only help a student to learn Machine learning but also become fluent in implementing it.

von Helen L

15. Juni 2020

Submission isnt easy often gave errors that are not due to students' faults. Time-consuming unnecessarily. The content and assignments are great.

von Utkarsh S

22. Juni 2020

Very informative course, the only issue I had was with the file locations in the assignments. Takes up a lot of time switching back and forth.

von Mariano T

18. Mai 2020

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