Oct 17, 2016
Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much
Aug 19, 2019
The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.
By Guelug T•
Jul 20, 2017
Un curso muy bien explicado, fácil de entender y unos profesores que consiguen mantener la atención y absorberte en el tema.
Lo recomiendo 100% para iniciarse en los modelos y entender los algoritmos simples de ML.
By Brian S•
Sep 27, 2017
Loved the case study approach and how it relates to real world problems. Utilizing graphlab also helped abstract away a lot of the details, but I look forward to diving deeper with the rest of the specializations!
By anirban d•
Aug 19, 2019
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.
By Shekhar P•
Apr 05, 2016
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.
By Aniket R•
Feb 06, 2016
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.
By Alessio D M•
Dec 07, 2015
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.
By Lin V•
Feb 20, 2016
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.
By Cristina E•
Feb 12, 2016
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.
By Hossein N S•
Feb 09, 2016
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
By Ethan G•
Nov 23, 2015
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.
By PRAVEEN R U•
Aug 23, 2018
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.
Jul 28, 2018
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.”
By Lokesh K•
Jan 27, 2019
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 .
By RAMESH K M•
Feb 08, 2016
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.
By DURGESH G•
Jun 21, 2020
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.
By ANIMESH M•
Jun 08, 2020
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.
By Muhammad H T•
May 04, 2020
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)
By Rania B•
Jan 06, 2019
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!
May 30, 2018
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 .
By Olga V•
Jul 07, 2017
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.
By Eik U H•
Jun 27, 2017
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.
By Lucas d L O•
Aug 09, 2016
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!
By Guillermo R•
May 13, 2018
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!
By Kan B•
Oct 24, 2016
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.
By Jeevanjot S•
Oct 29, 2018
Very good foundations course for beginners.....might be a little too basic for people who have experience in ML, but nonetheless good for refreshing your knowledge. Absolutely love the sue case approach.