Mar 17, 2016
I really enjoyed all the concepts and implementations I did along this course....except during the Lasso module. I found this module harder than the others but very interesting as well. Great course!
Jan 27, 2016
I really like the top-down approach of this specialization. The iPython code assignments are very well structured. They are presented in a step-by-step manner while still being challenging and fun!
교육 기관: Jerry S
•Apr 02, 2017
Really exciting course. The concepts are well explained and implementing algorithms by myself is really a inspiring experience. It is really a pity that the last 2 courses in the specialization were canceled. I am even willing to pay them for 100$ each!!!!
교육 기관: Ayush K G
•Sep 25, 2017
This course is full of information about regression in very simple way.
교육 기관: JOSE R
•Nov 18, 2017
Very well explained. Thanks
교육 기관: Saeed M
•Sep 21, 2017
great!
교육 기관: Tural I
•Apr 29, 2017
Just Great
교육 기관: Mohamed A M A E
•Oct 17, 2017
it is a good contant and i learn more information such as
Simple linear regression, Multiple regressionAssessing , performanceRidge , regressionFeature selection & LassoNearest , neighbor & kernel regression
교육 기관: Mohit K
•Apr 21, 2018
I found this course more useful as compared to the first one. I really like this. One suggestion here, I would like you to incorporate is that you must have given small project work at the end of this course. This course is more technical and it would be helpful if we do some live project.
교육 기관: Lalithmohan S
•Mar 06, 2018
Fantastic content, so much to gain from this
교육 기관: Ruchi S
•Nov 08, 2017
e
교육 기관: Christopher S
•Aug 03, 2017
Great course. Heavy on the math but could use a little more on the implementation side.
교육 기관: Le H N
•Jun 29, 2018
I gain many knowledge from this course . Excellent.
교육 기관: Dongliang Z
•Feb 05, 2018
very good course! I enjoyed it very much.
교육 기관: Shuang D
•Jun 11, 2018
excellent course on regression. great hands-on experience.
교육 기관: VITTE
•Jun 09, 2018
Great course.
교육 기관: Prashant M
•Sep 30, 2017
This was a very satisying course with the intensity and queries that challenge me and wish to learn more. I am quite excited to learn more with the new ML bug that has caught me! Liberating.
교육 기관: Jessie J S
•May 12, 2018
I love this course! It explains more about Regression itself and not just discussing on how to use libraries for it! Very intuitive and informative at the same time!
교육 기관: Ian F
•Jun 09, 2017
Great course - you'll become much more accustomed to Python if you aren't already (I'm an R convert) and really learn the principles behind regression analysis.
교육 기관: Alessandro B
•Sep 27, 2017
e
교육 기관: Hongzhi Z
•Feb 05, 2018
Very Vivid and learn a lots, best AI specialization in Washington university
교육 기관: Do A T
•Oct 26, 2017
very useful
교육 기관: Dipankar N
•Dec 11, 2017
Great course on Regression. This will help build basic for upcoming modules. Emily teaches the concepts in a simple way. I liked the structure and coverage of Regression topic.
교육 기관: Phil B
•Jan 29, 2018
This was the deep dive into regression that I was looking for, learning how and why to implement the various different algorithms that are used without being tied to a specific software package. Some of the other reviews complain about the use of graphlab but really it has no impact on the value of the course, because you can literally write the functions from scratch yourself using standard python and Numpy. The use of graphlab is just to speed things up in some of the programming assignments. One or 2 of the quizzes had some incorrect values in the notebooks but a quick search of the forums showed the correct ones and the ability to reattempt the quizzes means it's not a big issue. Emily is an excellent lecturer and the constant use of graphical aids and annotations makes it very easy to follow even with some of the fairly advanced maths.
교육 기관: Bruno R M
•Feb 02, 2018
Awesome!
교육 기관: Pavel P
•Jan 06, 2018
Just great!
교육 기관: SK
•Apr 02, 2017
This course is phenomenal! I am learning a great deal. Dr. Emily Cox is fantastic with her slides, explanation and the way she (and Dr. Carlos Guestrin) structured the course. Loving it!