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

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8,061 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

AS

26. Nov. 2020

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.

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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251 - 275 von 1,467 Bewertungen für Applied Machine Learning in Python

von Alexandre M

1. Feb. 2019

Good class, and it's very nice to have the "applied" machine learning angle (as opposed to focusing on the mathematical / theoretical underpinnings, which are only important at a much later point in time)

von Josh B

4. Feb. 2018

Excellent introductory course to machine learning using python. It covers the basics for the popular supervised machine learning algorithms. I'm excited to build on the knowledge this course has given me.

von Dongliang Z

21. Dez. 2017

Very good lecture for beginner:easy to understand.

Also good assignment: force you to use what you learned in the course.

The discussion forum is helpful when you meet difficulties in assignments and quiz.

von Steven L

8. Apr. 2018

Very practical introduction to using Python for machine learning - less focused on theory and more focused on how to use the sklearn library and proper use cases for different classifiers and regressors.

von Carlos D R

16. Dez. 2019

The course offers you a lots fot tools the face ML problems. There are few errors in the notebooks, but everyting is well documented in the forum. Good overview to represent data and train basic models.

von Giorgio C

25. Aug. 2017

The course is well structured and covers all the most important topics. The programming assignment could be a bit more stimulating. Overall I'd recommend this course to everyone who's interested in ML.

von Ewa L

17. Juni 2017

Fantastic course! Great foundation on scikit-learn. Really focused on APPLYING machine learning with just enough information about the models themselves to understand what's going on behind the scenes.

von Eduardo B

19. Juli 2020

Pretty good for those who are not too familiar with all the statistics that happens "under the hood" in a machine learning algorithm. The name "applied" suits very well in that way. Congratulations!

von Angelo S

20. Dez. 2018

An excellent resource to immerse yourself into machine learning methods. Professor Kevyn explains key concepts in the most intuitive way possible. It does require some previous experience in Python.

von Fernando T

28. Apr. 2021

Complete course about (mainly) supervised machine learning. Several classifiers and regressors and explained and compared. Appropiate assignments to test the understanding. I recommend this course.

von SHREY S 2

7. Nov. 2021

Great experience i learned a lot in machine learning in python with different terminologies used in applied machine learning. I understand each and every topic which was told by Kevin Collins Sir!

von Petko S

3. Apr. 2018

Extremely useful course! You really get a lot of value from it and exactly what you would expect from such course! Very entertaining and a lot of additional educational materials! Thank You a lot!

von Shashank S S

19. Aug. 2017

the content of videos , quiz and exercise all work extremely well together towards the stated goal of the course i.e. to give the learner a good over view of how to apply ML theories into action

von Michael B

19. Juni 2017

Not for the faint of heart and some experience with Python, in particular Pandas, is preferred. Great overview of the different methods used in machine learning. One of the better courses imo.

von Brett S

18. Sep. 2020

Great content and good instruction. Need to fix the files in the assignments though. It's hard to keep track in the forums and frustrating go back and forth to find out why it's not working.

von PRAKHAR K J

13. Apr. 2020

It feels good to learn something new and highly skilled demand in Engineering. Thanks to Coursera and instructor for providing such a wonderful opportunity of learning through your platform.

von Jens L

20. Aug. 2018

Concise and clear presentation of the material with the majority of time focused around using TDD to learn and practice concepts through developing solutions to open ended coding challenges.

von HAGE M

24. Okt. 2021

It was good learning Machine Learning thru Python as using Python libraries like Pandas , Tensorflow,.etc made the work easier. Hope to do my masters in Machine Learning . Happy Learning <3

von Amithabh S

23. Juni 2017

Excellent course for someone who already has some knowledge of python but not quite familiar with machine learning. This course will teach you the application of machine learning in python.

von Abdirahman A A

13. Jan. 2019

In depth course that covers a lot in a short amount of time. If you take some extra time to delve deeper into these topics, you can ensure a great overview of machine learning with python.

von Marcin K

11. Sep. 2021

Quite detailed; good instructional material about most ML models and evaluation metrics of models, cross validations, grid searches, precision and recall curves etc. Excellent assignments

von Diego A L B

22. Okt. 2020

EXTREMELY USEFUL AND GOOD COURSE, CONGRATULATIONS TO ALL THE PEOPLE INVOLVE.

Honestly, I never thought I could learn so much in an online course, excited for the rest of the specialization

von RAMANA V S B

24. Feb. 2022

its a very great course i have ever seen, because it a applied ML it will avoid all waste of theory and statistics and complete focus on main points and coding part within very less time

von Indrajit P

29. März 2020

Very well structured and informative course ! All the lectures are concise and give enough context for self-exploration. The assignments provide are a good hands-on experience as well !!

von jay s

15. Juli 2017

Excellent lectures, good exercises to reinforce the material, and absolutely loved the explanations of the sophisticated mathematical models that made them more lucid and easy to digest.