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

4.7
stars
3,438 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

MK

May 18, 2021

The course covers all the topic's regarding the machine learning and has an excellent explanation of concepts and the slides are very easy to understand thank you for such a wonderful course !

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26 - 50 of 809 Reviews for Introduction to Machine Learning

By Prajwal K

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Apr 26, 2021

Just learning the course and loved it coz of its depth in knowledge in Machine Learning.

Week 1 covers almost all fundamentals topics and lays the solid foundation to the learner in ML.

Looking forward to enjoy learning this course attentively, complete the assignments.

By Fahad K

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Jan 25, 2021

I suggest to every who is interesting in online course , should study with coursera.org.

They will teach you in a such that all your doubts will be cleared.

They have quiz and assignment at the end of lecture.

So I strongly recommend this to every one.

By JONATHAN F G H

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Aug 9, 2020

The concepts presented are very clear. I understand a little more about machine learning thanks to the course. The support of the concepts using PyTorch was also an interesting aspect in terms of integrating theory and practice.

By Leonardo M

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May 12, 2021

I simply loved the course. I've been working with Machine Learning, but I didn't understand much about Deep Learning - this course helped me a lot to get started in this new research area.

By ANKUR O

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May 7, 2020

This course give a good introduction toward machine learning and AI. someone who wants to pursue his/her career in ML and AI in future this course would definitely help him/her

By Riley B

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Jul 30, 2019

I liked the pace and the tensor flow applications. This should be upgraded to TF 2.0 at some point. Also, I would've appreciated some GAN material.

By Ayse U

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Nov 11, 2018

I like this introductory course, very good one to start to learn machine learning. I will definitely continue studying and re-watch the videos.

By Tunde O

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Apr 21, 2021

Very instructional with lucid explanations, the hands-on practical or lab sessions helped me to actually practice what I have learnt.

By FERNANDO G M

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Jan 12, 2023

It is a good and awesome course because it takes you by hand from the basics of ML to the most complex models.

By Sameera K

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Sep 19, 2018

Very Good course explaining the theoretical concepts related to deep learning . Thank you

By Tarun Y

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Apr 22, 2019

A very fine tuned Course,used as a warm up course for deep learning,highly recommended

By EX_TE_15_ P S V

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Aug 22, 2021

It was very good , understood all concepts and learned something new.

By Sean C

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Dec 23, 2020

Labs are great hands-on training, but the lectures and lab texts don't sufficiently prepare the student for the assignments. Watching them and reading the text will not give the student the skills to solve the assignments, forcing the student to search online for a better tutorial. I recommend providing the complete code to create a MLP, CNN, SWEM, RNN, LSTM and GRU.

With a basic template created, the lab questions can then have the student change epochs, batch sizes, etc.

I am aware that some basic templates were provided, but providing a SWEM and having the student convert it to a RNN is a huge jump. I took detailed notes during lectures and read the lab notes, but ultimately had to find other resources to complete the assignments, because the answers were not provided by this course.

I hope this critique does not come across as a personal attack. I teach electrical engineering and understand how difficult it can be to fully explain complex topics. Thank you, all four of you, for creating this course!

By Dziem N

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Apr 22, 2020

I would like to thank Prof. Carin for a very lucid and intuitive explanation of the major concepts in Machine Learning covered in this class. This is the best explanation of the concepts of CNN and Reinforcement Learning that I have found so far !!!

I am also a little bit disappointed by the set of Programming Exercises at the end of some the lectures by other teachers. I think instead of giving students examples of programming using raw, low-level TensorFlow APIs because it overwhelms the main concepts. It is better to use high-level back end tool like Keras (NOT Slim !!!)

By Nam N

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May 12, 2021

Course gives us the fundamental knowledges of Deep Learning (mainly) and Machine Learning, I see it very clearly and easy to understand, the Instructors are very dedicated, especially Larry . But the disadvantage of this course is that you maybe gain nothing about Pytorch, as all the lab/assignment are optional. Yeah, there are no practical lesson at all!

If you are the type of learning-eager, this course is also good for you. But if you want more pressure in learning that needs you to exert, I will not recommend it.

By Chen S

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Feb 24, 2020

It is a very basic introductory course to important fields in machine learning. It tells important models like CNN and RNN and LSTM. but it does not go deeper into the technical levels of these models. Some parts about mathematics are not very satisfying. Also I feel like the course doesn't provide enough training for the coding work. Nonetheless, it is a good course to start with machine learning and the instructors repeat the concepts from the previous class, which helps me a lot in understanding the concepts.

By Brian L

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Jul 5, 2022

A simple intro to deep learning concepts, good for beginners. The code exercises are also a good springboard into using PyTorch, but they could've matched the lectures a lot better. For example, I would've liked "Build a NN from scratch" instead of just "Use this library".

By Alexander D

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Nov 6, 2023

Great content, but would have been nice if there were downloadable lecture slides for all lectures (not many for Week 4), and if some of the broken links in the labs (e.g. for downloading anaconda) were fixed, as well as bringing the labs up to date.

By Noah R

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Apr 5, 2019

Great course for beginners, did a lot to fill in the gaps in my knowledge. There could be a little more help with the actual coding parts of the project, the work done in ipython notebook is largely self-taught.

By Kleider S V G

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Aug 24, 2021

A good introduction to Machine learning, literally!

By Ahmad H

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Aug 28, 2021

Wonderful experience and learning environment.

By KAVADIBALLARI V

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Oct 24, 2018

GOOD COURSE

By Sunita R

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Jul 12, 2022

I like Coursearas courses, This course is also very well, I clear mu many concepts from here.

But the issue I find with this is that the lab activity is not organised in well manner. Because I can't understand the codes because of that I can't do code by myself. Reason is just no one can understand the code who are not familier with some new modules of python. So if lab activities are organised in also same vedio type material, where a mentor teach about that how that code is work, this is better idea I think so.

I hope you will work on this and provide me a vedio session on coding parts.

All other things are too good mentor, there ppts and there way to explanation are fabulous.

Thank You

By KRITHIKA G

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Jul 16, 2020

The codes can be explained in videos rather than giving them in texts in the open lab. This can make coding even more understandable and applicable.

By Orestis K

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May 15, 2021

i would prefer to be more practical, and the lectures to be step by step on how can practice machine learning in real dataset (problems). I see that generally coursera emphisises in the theory rather than practical.

When I came up to the assesment I quit, because I had to spend so much time to understand how the framework works.

I would say that is a course with traditional acadademic lectures, which is not my type.