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Learner Reviews & Feedback for Introduction to Machine Learning by Duke University

4.7
stars
3,625 ratings

About the Course

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 reviews

KS

Aug 4, 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

Nov 26, 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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801 - 825 of 832 Reviews for Introduction to Machine Learning

By Viktor B

•

Jun 24, 2021

It's an introductory course, so what you'll get is an intruductiory overview. During the lecture videos, you'll have to take some things for granted. Some of them are explained later, some are not. What I do mind is that there is no interaction between the course staff (lectures or assistants) and course participants. So some of your questions will be left unanswered, and on some you'll get questionable answers. More and more I find this to be the general problem with Coursera. You have few graded quizes and few lab exercises. So in my opinion, the course is not worth paying extra money for the certificate.

By Evren O

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Jul 22, 2021

I enjoyed Lawrence Carin's explanations a lot but the overall experience was not great I'm afraid. It felt like it did not come together properly. The order of lectures and assignments felt wrong. The Python level of competence was too high for this course and support (via forums) was non-existent. I don't regret finishing the course but I would not recommend it to my friends.

By Grace F E P

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Apr 28, 2021

The lectures were great and very easy to follow! However, I found that the assessments were too easy as they comprised solely of multiple choice questions, maybe including hands on coding assessments fo contribute to our final grade would have made me feel more confident that I've grasped what was supposed to be taught to me each week.

By Vaibhav B

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May 2, 2021

Modules need a bit of synchronization.

Please spend some more time explaining gradient descent.

If possible, explain using a board where we could have things simultaneously.

Also, request to have a course on machine vision using CNN etc.

By Hanyou C

•

Sep 20, 2023

Good introduction to the concepts of machine learning. Somewhat overly repetitive, some inconsistencies. Information is not up to date, for example, the python code for Tensorflow would not work.

By Aditya Y

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Apr 30, 2021

This course is good for just theoretical understanding of the subject. But for practical implementation it is too hard to do.

By ANETTE A

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Jun 10, 2021

Thank You team Coursera and Teachers from Duke University for helping me to understan dthe basics of machine learning..

By mehrshad b

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Apr 23, 2021

More examples should be provided for each course, and the content needs to be more simplified.

By Venkat D

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Apr 9, 2023

A bit too technical for new learners. More practical exercises will make it more learnable.

By Yusuf

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May 23, 2020

The theory is well explained but you guys should update the coding parts to TensorFlow 2.

By Gman

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Oct 6, 2022

There are many better ML intro courses out there...poorly structued and delivered.

By Shaurya A

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Aug 2, 2023

Only concepts no practice. But the concepts are really well taught according to me

By Farrukh G

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Jan 11, 2022

The course requires more detailed intuitive approach towards material preparation

By Karnati S A

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Jun 8, 2021

some concepts were difficult to understand and not explained very well

By Anand S

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Jun 20, 2022

just a basic overview of the methods. not much worth the time

By Laura S

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May 17, 2021

I could not even understand the introduction class

By Sarah G

•

Sep 1, 2019

Pretty good introduction to Machine Learning!

By Athar A

•

Sep 26, 2024

Overall good experience

By MITHILESH K R

•

Sep 13, 2020

4.2

By Oleksii Y

•

May 18, 2024

I rate the course after "2 weeks' finished. The course is strictly theoretical, but it doesn't give you enough infomation on a subject. You can gain the same knowledge from YouTube and it will be even faster. I don't know why would somebody pay for the course. But, the course is better than Netflix, so it could be a great thing to watch while eating your meal.

By Chakshu .

•

Mar 26, 2023

Although the teachings of machine learning are introduction. A learner needs to know moderate level of python and pytorch to continue the course fluently.

By Liona L

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Oct 28, 2021

The concept is taught ok, but it's not great on hands-on learning.

By Luis S

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Jan 26, 2022

Topics are explained in a random and ilogical fashion. For example, they teach CNNs before gradient descent or the basics for training a model (like training splits or criteria to evaluate a model). Lack of order, toghether with confusing figures and poor metaphors, make impossible to properly understand any concept, and that can be seen in the discussion forums. In addition, there are gross conceptual errors, like suggesting that problems with non-linear solutions requiere NNs and can't be solved with linear regression algorithms. In fact, the whole course is centered in neural networks despite being presented as an introduction to ML and sells the idea that somehow NNs are the ideal solution to any non-trivial problem. This course is in shocking contrast with some other excelent courses that can be found in this pplatform, like the ones from Standford or Michigan.

By Jose V A S

•

Nov 6, 2021

muy poco ejemplos prácticos que se puedan seguir la momento de la explicación, hablan de una manera muy general pero no no dan ejemplos explícitos de su uso. no muestran como se transforma una palabra en un vector, el único ejemplo con el que se logra entender lo que esta realizando es el ejemplo inicial de los triángulos desplazándose sobre los filtros y las imágenes, en el resto de temática nunca aterrizan sus ejemplos

By Fabián G F

•

Nov 8, 2021

From my point of view as student who completed all weeks:

-The forum is totally dead. Nobody answers the questions since months. No support.

-You will not have a feedback of the assignments that you do.

-Confusing explanations. The order is not the correct

-Very theoretical and few practice.

You will need to search on internet other explanatioins to understand some parts. Hope standford course is better.