TH
14 de mai de 2022
This is an excellent course which goes into some depth on the different ML models and underlying complexity but it avoids getting bogged down into the details too much.
SK
11 de abr de 2020
Excellent course. In which I had in-depth knowledge of all algorithms and the way she explained attracts to listen except for her spontaneity and speed in progressing.
por KAZI S S
•14 de jun de 2020
although the course felt a little hurried, I found the course and the instructor to be very engaging. I look forward to learning more
por Enyang W
•21 de fev de 2020
This course covers lots of important ideas and knowledges for Machine Learning practitioners. It is definitely nice to deal with topics such as grid search or scikit-learn, but I think the course only covers these topics in a nutshell, it is more superficially discussed. If you are interested in Machine Learning, you should definitely bring your own motivation to dive deeper into those topics.. Also, Dr. Koop speaks very very fast though.. I attended courses by Andrew Ng, his courses provide a way better comprehensibility for listeners. The notebooks are a bit weird, very easy to understand and are hence not challenging. If you really want to understand the algorithms deeply, I don't think this course is the right one. But all in all, I completed the course, but I don't think I was able to understand everything by taking the course only.
por Luiz C
•11 de set de 2019
Had higher expectations. Concepts not well and clearly explained. Notebooks bugged (we are actually warned about it), but even so not so interesting. Plan of the Course not so rational: why include the one section about model parameters on its own, rather than for each model.
I give it a 3 as the Instructor is smily and engaging, but it's a 2.5 mark (I have done another ML MOOC on another concurrent platform about the same topic, and the quality was much higher)
por Varun M S
•25 de jun de 2020
The content was good but the videos went too fast and too much theory was involved. For a beginner it was too much to take. I was expecting some Practical and programming aspects in Quizzes and tests but that is okay. Overall a good experience
por BINSHUANG L
•15 de dez de 2019
Good coverage of the topics in supervised learning. However, lacks depth in some of the concepts.
por Efren C
•13 de jan de 2020
Excellent course, I was looking for a course which didn't explore advance math or go into the specifics of a particular ML method but which focuses on the main differences among then and teach about the whole process of M, this is the best course for that.
por Tino v d H
•15 de mai de 2022
This is an excellent course which goes into some depth on the different ML models and underlying complexity but it avoids getting bogged down into the details too much.
por S. k
•12 de abr de 2020
Excellent course. In which I had in-depth knowledge of all algorithms and the way she explained attracts to listen except for her spontaneity and speed in progressing.
por Dishant S
•7 de mai de 2020
Excellent course for an overview of different ML algorithms. The course is made from a perspective of giving insights in process and not too many mathematical details.
por Ram M
•9 de dez de 2020
I found the course to be enough detailed to get clarity on the basic concepts of Supervised learning algorithms. I hope to apply the learning from the course in work!
por Chih-Ta W
•30 de set de 2020
Great course, easy to grasp the main idea of how to assess and tune the performance of question-answering machines learned by machine learning algorithms through data
por Alvaro V
•11 de jul de 2020
Very important concepts about supervised ML are presented. Really liked the course but a little stressed about the graded quices, even though I enjoyed very much.
por Fahim F
•17 de abr de 2020
Great course but less in-depth knowledge about each of the hyper parameters and under the hood view of Algorithms.But excellent. Thanks!!!!!!
por Sornamuhilan S P
•19 de jun de 2020
A great short capsule course to get overall bird view on Supervised learning. Much needed one for both practitioners and new beginners.
por Bishrul H
•5 de jun de 2020
It's a nice course for those who likes to learn the supervised machine learning algorithms with practical experience.
por Kevin A D G
•10 de mai de 2020
The explanation of the topics are easy to understand due to the dynamics of theory, practical exercises and quizzes.
por Vinayak D
•1 de set de 2020
really good, wish it had covered random forest and decision trees and other supervised models as well.
por Emilija G
•9 de jan de 2020
The whole specialization is extremely useful for people starting in ML. Highly recommended!
por Munem
•23 de jun de 2020
Easy and engaging. But would loved it more if some more coding examples were given.
por Brett S
•4 de out de 2020
Excellent instruction. One of the best in ML. Could use a bit more python though.
por Valery M
•31 de mar de 2020
Nice course! Good idea to add more practice with Jupyter Notebooks!
por Morgan J
•30 de out de 2019
Great course! I received so much useful information from AMII.
por Miguel A S M
•15 de out de 2019
Excellent.
Teach you practical stuff that other courses don't.
por Hamza M
•2 de mai de 2020
A good refresher on some commonly found learning algorithms.
por Gustavo I M V
•2 de dez de 2020
It was an excellent course. Thank you! You are a master!