워싱턴 대학교의 Machine Learning Foundations: A Case Study Approach 학습자 리뷰 및 피드백

This stream along with Andrew NGs is the best ML course available in Coursera. The lectures, especially from Emily's are one of the best. It is perfect for both experienced and newbies. Thanks, Emily and Carlos.

Awesome course ....Both Professors are very intelligent and teaching perfectly....Step by step explanation and also never feel bore because presentation styles are also very best. Thanks professors and Coursera.

The case study approach makes it fun to learn machine learning. The introduction to various topics through specific examples increases curiosity and sets the tone for the following courses in the specialization.

Thoroughly enjoyed this course! Really loved the case study approach of teaching. The instructors are excellent as well, throughout the course it felt like I was hanging out with my friends building cool stuff!

I think the course is really COOL :) I know that it's really hard to cover so many topics, but I would have been curious about the area of reinforcement learning too. Perhaps mentioning MDPs and related models.

Thank you very much for providing us this cool and exciting course. Thank you, Emily and Carlos. It opens a door for me and I've really enjoyed ML so far. Hope one day I could be part of the UW. All the best.

Very good explanations and well-thought out assignments and practical exploration. The usage of the proprietary GraphLab software was a minus, but since it was used just for exploratory purposes, no harm done.

This course was very usefull tome as it was implemented in a way that it's easy to understand the core of the module and the subject.

I understand and it prepared me for the rest of the Machine Learning courses

This was a great intro course to the topic, and the instructors both make complicated concepts accessible. For example, the explanation of non-linear features in deep learning is extremely clear and intuitive.

This will be really helpful for someone who really wants to start the ML journey and not sure where to start. The content was designed well to suit people across levels and technologies. Strongly recommended.

To define how machines can learn, we need to define what we mean by “learning.” In everyday parlance, when we say learning, we mean something like “gaining knowledge by studying, experience, or being taught.”

Pretty Cool as Foundations in ML!!! If you already have expertize on Pandas and python you would find this course as a good entry point for Machine Learning as the point of view is 50/50 theorical/practice.

Friendly introduction to basic concepts and how to put them in practice to start diving into the exciting ML world that is all around us nowadays, specifically during current uncertain and challenging times.

I appreciate the effort you kept for this online course.Actually I enjoyed learning here.But you can be little bit more detailed in the ipython notebook code explanation. Otherwise ,this is the best course .

Course is really taking a practical approach towards machine learning, with theory and practical classes side by side. Thanks to Course era and University of Washington for providing a wonderful opportunity.

This course will provide a deep and elaborated knowledge about basics of machine learning and deep learning. Both the instructor Emily And Carlos are very good they cover each and every point of discussion.

Such an amazing course.

It opens all the uncovered secrets behind Machine Learning .

With best mentors and enough practice i had gain thorough knowledge and interest toward Machine Learning.

Above Expectation.

Amazing course by Carlos Guestrin and Emily Fox both have the deep knowledge of their domain and more over they also have the skills of how to teach. Love you both Carlos Guestrin (Sir) and Emily Fox (Mam)

I had to use TuriCreate instead of GraphLab, so other than the changes in the libraries that had me guessing which function to use, everything in this course is well structured and concrete. Thank you all!

Actually, this course is the best introduction for machine learning for me .

it gives me a outline of machine learning structure . thankful , and i will continue learn other courses in this whole course .

Great course giving an overview helping get a sense how machine learning is applied. Material is delivered well and concisely. Like the data sets used for examples, because they are interesting to explore.

A real breathtaking great course about the basics of machine learning with very concise materials. Unfortunately died after four parts. I'am hoping for resurrection with a part 5 and 6.

Thank you very much.

Great course for understanding introductory principles of the different areas of Machine Learning. The classes are very well taught and the exercises are very interesting. Highly recommended for beginners!

I really enjoyed the foundations course. It did exactly as I expected - it gave a great overview of machine learning concepts to prepare for the upcoming in-depth modules. Emily and Carlos were fantastic!

Very good approach. Let students hands on and play with ML model first, before jumping into details. In real life, understanding use cases is really important before investigating more time into theories.