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

7,973 Bewertungen
1,452 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....



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!!


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

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1276 - 1300 von 1,442 Bewertungen für Applied Machine Learning in Python


1. März 2020

Its a very good course for an intermediate level.

von Vinay P d L R

26. Sep. 2017

goes too fast and too shallow to deserve 5 stars

von Adesh T

8. Feb. 2022

It was amazing journey to complete this course.

von Prerna A

27. Apr. 2021

The course is planned in a very structural way.

von Anendra G

30. Apr. 2018

Awesome theory about machine learning concepts.

von Catherine M

1. März 2021

Nice course. A lot of ML models get presented.

von harsh a

3. Feb. 2018

Good course.

Thanks to entire team

Harsh Arora.

von Tianyu Z

19. Juni 2019

Some concepts should be introduced in detail.

von Amita D

18. Mai 2018

Need more information about more algorithms


16. Jan. 2022

Excellent way of teaching and learned well

von Souvik M

23. Jan. 2022

where is my certificate?????????????????

von Ruben W

8. Sep. 2019

Best course so far in this specialisation

von Alan F

28. Feb. 2018

Good course but there's a lot of material

von Abdulwaheed M

17. Juni 2020

Teaching is very good and it is helpfull

von Alperen B O

16. Dez. 2020

I get late feedback for lab assignments

von Ramya K

15. Juli 2019

Well-organized but assignments too easy

von Supratim D

10. Aug. 2017

Very informative but bit too difficult.


2. Aug. 2020

very helpfull.thanks for creating this

von Xiang C

12. Mai 2020

It's good to learn how to use sklearn.

von Jagadish C A

19. Sep. 2019

Gives good overview of ML using Pyton

von Shreekant G

17. Juli 2019

Really taught best ML algorithms

von xingkong

9. Aug. 2017

quiz is harder than assignment.

von shreyash t

28. Juli 2020

overalll good way to start ml

von Vaibhav S

27. Mai 2020

way better than last teacher.

von Nicolas B

5. Juli 2017

Muy buen curso, muy completo.