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Bewertung und Feedback des Lernenden für Introduction to Machine Learning von Duke University

4.7
Sterne
3,048 Bewertungen

Über den Kurs

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction. In addition, we have designed practice exercises that will give you hands-on experience implementing these data science models on data sets. These practice exercises will teach you how to implement machine learning algorithms with PyTorch, open source libraries used by leading tech companies in the machine learning field (e.g., Google, NVIDIA, CocaCola, eBay, Snapchat, Uber and many more)....

Top-Bewertungen

KS

4. Aug. 2020

I felt that I took the best descition in taking this course, because the professors took this course with atmost clarity and made even the difficult concepts understand easily.

Thank you Professors

NN

26. Nov. 2020

Thanks Coursera and Duke University for this course. It is very insightful to get understood the basics of ML and applied ML in numerous fields. It really made me to move ahead with ML domain.

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551 - 575 von 731 Bewertungen für Introduction to Machine Learning

von deepika h

24. Apr. 2021

Good

von vaibhav t

23. Apr. 2021

good

von madhumitha.c

20. Apr. 2021

Good

von PREETHA R

19. Apr. 2021

good

von RUBANSRI U

18. Apr. 2021

COOL

von ARPAN M

17. Apr. 2021

good

von CHEKKA S S S K

6. März 2021

good

von Dr. S V

6. Sep. 2020

good

von AARTHI 1

5. Sep. 2020

good

von Sunidhi k K

29. Juli 2020

Good

von SAYANTAN D

28. Juli 2020

Nice

von vaibhavi u l

19. Juli 2020

good

von ARAVIND K R

12. Juli 2020

Good

von PREETI.R

9. Juli 2020

GOOD

von Vikash k

20. Juni 2020

good

von Narendra P M

2. Juni 2020

Nice

von SHIVAKUMAR S R

29. Mai 2020

good

von Katha C

18. Mai 2020

good

von Dr. S C

4. Mai 2020

good

von vinayak b k

27. Apr. 2021

nil

von Sayan G

20. Sep. 2020

A++

von arun

3. Dez. 2021

Ry

von SHEPHALIKA

14. Mai 2022

.

von 19-315 P

14. Jan. 2022

g

von Paul O

16. Nov. 2021

The course aims to describe the key elements and techniques of machine learning but without delving into the associated maths. It manages to achieve this. The first lectures are delivered in a somewhat hesitant way but they improve over time and provide some very good insights as to how the procedures like convoluted neural networks work. Having only previously had exposure to Andrew Ng's Introduction to Machine Learning Course, I thought this course was a useful complement to the Stanford IMLC course.

So why not five stars? There were a few annoying things that could be improved IMHO:

1. The course is six weeks long, but there are only tests for the first four weeks. Once you complete these, you get messages saying you've completed the course, despite there being two (rather important) weeks left...why not have tests for the last two weeks of content??

2. The computing assignments are not graded, but there is no prior indication that this is the case! Probably just as well, since they assume a degree of familiarity with Python and Pytorch that is beyond the casual computer-literate person (though the Pytorch website provides lots of relevant help in this respect!) but it would have saved lots of angst to know that these were in effect optional.

3. The discussion boards are not reviewed by the course providers; numerous student questions are left unanswered, unless other students help. This is in sharp contrast to the Stanford course, where the discussion boards are very active and tutors are on hand to help and provide guidance.

But all in all, a useful and enjoyable course for a novice like me.