Great course! I like their approach of describing application first and then trying to use a fairly complete approach. Submissions in the form of quizzes and auto-graded assignments work better as one does not have to wait for other people to complete the course at the same time, which might be rare at the beginning and end of the session.

Great introductory course to ML! I learned some valuable insights by building actual models using GraphLab. After taking this course, you'll have the foundations and overview of machine learning to take the follow up courses in the ML certification by same instructors or take any other ML course available out there. Highly recommended.

I really liked the case study based approach of this course. It makes you hit the ground running by applying the concepts learnt in a lesson in the case study immediately. I also like the light hearted tone of the teachers - Emily and Carlos, which helps in retaining interest through some of the more challenging concepts in the course.

This course is the right choice for someone who wants to get a high-level overview of the various fundamental concepts in machine learning and provides the zeal to pursue further. Concepts have been explained by the lecturers really well and quizzes and assignments help us to validate our knowledge of the concepts in a seamless manner.

This course is a great way to get adequately detailed knowledge of Machine Learning Algorithms. The approach to it (case study based) makes it so much more fun and enjoyable that you can really apply yourself to it. The professors have simplified the most complex topics and explained it amazingly well. Happy to have taken this course.

A very very awesome course with exceptional explanations for each machine learning paradigms and use cases. The best thing for the course was the case study approach. I am taking this approach to train my people as well but over all thank you Carlos and Lady.. for the effort. Really hands on python and machine learning experience (Y)

Very good course, I enjoyed the way the instructors structured and presented the material, in both a professional and personable manner, and the use of case studies to help solidify the knowledge. Assignments were very well built; although they used quizzes, it really required some thinking and prep work to get the answers right.

This course has excellent content which is very relevant to Machine Learning practice in industry. However the assignments are little easy. I think this is because this is a case study approach and like an introductory course. I would strongly recommend this course for a beginner who want to learn how ML is being used in industry.

It was very nice experience. Prior to the course, I heard about most topics. This course helped me to structure the ML concepts in my mind. I like learning by doing. The assignments in the courses really challenged me and I learned good practical knowledge. I am a beginner to MOOC courses, this course was a good start. Thank you.

It's a great course as first approach to this fantastic world "machine learning". It provided to me a general overview about the potential and the state of art of that technology. This course fired up my curiosity to "deep learn" about mathematical concept behind the scenes and I very hope next courses can cover that knowledge.

One of the best courses that I attended so far in Coursera. If you already attended the Machine learning course from Andrew Ng or you have some idea of what is Machine learning about, this is the perfect next step. Explanations of machine learning 'buzzwords' and real python examples. Instructors are great. Highly recommend it!

I loved it! This is all I can say in a word about this course. The taught topics were awesome, interesting and useful in practise. If I was supposed to recommend a machine learning online course to one of my friends (especially if he/she didn't have a previous background), this course was the absolute thing I would've suggest.

Excellent course, really appreciate the your hard work in creating easy to follow course, very good slides and presenting information and explanations step by step.... oh and also love the on-screen chemistry between both of you and engaging style with students. It has been an enjoyable course. Please keep up the good work.

This was a great introductory level course to machine learning. It was very practical and allows for one to really start employing ML techniques quickly without getting too bogged down by theory. It was a pleasure working in Python and with GraphLab for this course. Looking forward to the next courses in the specialization!

I learned a lot from this Machine Learning course! It was rather general, but that was what I expected from the first course in the series. In my opinion it was worth the money as the quality was high and it provided an extremely good starting point in this area. I'll definitely be purchasing the next course in the series.

Great course. I really enjoyed going trough all the classes with Emily and Carlos. The case study approach is also very compelling. Loved it and really recommend it to anyone curious about ML.

Some previous experience in Python is required, which I hadn't, so I had a quick Codeacademy python course that really worked well.

Got the best course so far to introduce me to the concepts of Machine Learning. Kudos to the instructors Emily and Carlos for providing a well laid out syllabus with an approach that was grounded on practical concepts and demonstrating hands on with real world examples. Hoping and requesting them to keep up the good work.

This course offers a broad range of examples in ML. Clearly some basic knowledge of linear algebra and other concepts is needed, but I believe it is well structured to help those who're not so strong in math. It really is basic, though, so if you have already some knowledge in ML this will result sometimes a bit slow.

This is a very good introduction to ML. I felt that everything was presented in a very straight forward manner. A little more guidance on installing python and jupyter would be beneficial for those that have not used python packages much.

Overall a great course and I am looking forward to the more in depth courses :)

Great overview and engaging introduction to regression, clustering, classification, and deep machine learning with hands-on ability to see some of these practices in action programming exercises in Python. Good introduction to the more in-depth materials which will be covered in other courses in the specialization.

A good course for a specialisation. I faced Little problem in downloadins of graphlab,turicreate,matpotlib .as it was mention to download only turicreate.........but I had to download all graphlab and matpotlib. But the trainers were just awesome. Explanation of the Topics with examples were really understandable.

This course is very interesting and teaches you the basic concepts and practice applications of machine learning technics. The only drawback is that this course rely heavily on graphlab package which cannot be used in Python 3.7. Took a long time to search for alternatives in sklearn instead to finish assignments.

This is an excellent course... One can tell that a lot of effort went into making this course fun and easy to work with... Almost certainly the most fun to work on course I've taken on Coursera so far... The instructors are very nice, the video lectures are fun and the assignments are easy and fun to work with...

It was greate and complete foundation course on ML which i have taken by University of Washington department. The lectures are very clear and can adopt to the real world problems. i am very much thank full to the faculty for such an wonderfull case study approches given in the entire course.

thank you once again.

Excellent course and highly recommended - covers fundamentals, TF-IDF, cosine. jaccardian similarities, recommender systems (precision/recall, AUC), deep learning via transfer learning (not having to explicitly build a model for the problem).

Exercises could be done in some tool which is common across industry.