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

8,254 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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1301 - 1325 von 1,500 Bewertungen für Applied Machine Learning in Python

von Jeffrey D B

16. Okt. 2018

Pretty good class, decent but very quick walk-through of ML tools.

von Arun P P

29. Juli 2020

It was n insightful course but was quite advanced for a beginner.

von Manuela D

8. Aug. 2019

Well organised, lots of details, a good overview of ML algorithms

von Sang L

28. Juli 2018

Speed kinda fast but maganeable. Need more detiailed notes/slides

von Lasal J

29. Dez. 2020

The content is great, I wish if there is more support in forums.


4. März 2021

Amazing Course for those who need to take the next step in ML.

von Vatsal M

26. Mai 2020

Some of the assignments have bugs in them please rectify them.

von Jose I B L

30. Juli 2020

Good coure, need more feedback in the quizzes and asigments.

von Sai A D

13. Okt. 2019

pre-processing and unsupervised learning needs more emphasis

von Deleted A

13. Juli 2018

there are some gaps which is really difficult to understand!

von Xingyu W

13. Okt. 2019

Need a better configuration for homework data file loading.


22. Mai 2020

allowed me to hone my knowledge of machine learning models

von Jason A

26. Juni 2018

This course was tougher than expected, but I learned a lot

von Bernardo A

8. Juni 2017

Great content and good assignments! Learned a lot from it.

von Gururaj N k

11. Nov. 2021

overall the course was good and has good content of data.

von Manoj B

2. Juni 2020

Decent course. I'd call this, 'Intro to Machine Learning'

von Antti H

23. Okt. 2020

Good course, but the labs have quite a few bugs in them.

von Wang Y

16. Feb. 2018

Good, despite some confusions in the lecture and quiz.

von Tangudu S S

23. Mai 2020

Got a very clear picture of ML usage in Data Science.

von Yash B

7. Mai 2020

It was little bit difficult specially the assignments

von Abhishek R

27. Mai 2018

Needed a better retrospect on final/week 4 assignment

von Varun S

30. Aug. 2022

Lot's of problems with automatic grader. Please fix.

von Alexander C

11. März 2018

Good introductory course. A lot of material covered.

von Dr. F T

17. Aug. 2018

Good but I was expecting much details in some area.


1. März 2020

Its a very good course for an intermediate level.