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

3,041 Bewertungen
709 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)....



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


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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726 - 731 von 731 Bewertungen für Introduction to Machine Learning

von Artyom L

19. Apr. 2021

Question 1 Quiz 1: Why is machine learning exciting? Really? Glad that's a free demo course, otherwise would've been a waste

Can't speed up the video. Speaker's too slow

von Divyen M B

19. Apr. 2021

Do not like how I cannot unenroll myself even if I see how this course is something I am not being able to manage.

von Shivani J

27. Apr. 2021

I dont have the requird skills for the course and now I am unable to unenroll from the course.

von Mike C

30. Apr. 2021

Very advanced for an introductory course in my opinion

von Abdul N B

20. Apr. 2021

Please cancel this course. I want to opt out of it

von Muhammad A D I M

23. März 2020