Mar 01, 2017
Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.
Jun 18, 2018
Excellent introduction to basic ML techniques. A lot of material covered in a short period of time! I will definitely seek more advanced training out of the inspiration provided by this class.
By Premkumar Siddharth•
Mar 16, 2019
Great course and farily challenging exercises! Thank You for putting this together!!
By Sakib Shahriar•
Mar 15, 2019
Include more swirl practice problems.
By Paul Ringsted•
Mar 13, 2019
A key course everything has been building towards, some important concepts and modeling techniques are introduced. However Jeff rushes through a lot of material, and I think this would be better served as two courses with more case studies and exercises, especially as the capstone doesn't use much of this. But nevertheless a useful introduction to this topic, concepts of training vs. testing etc, different models to be used, along with the caret package in R.
By Yap Yanliang Amos•
Mar 11, 2019
Instructor was clear in his explanation. Would prefer to have more hands on exercise for practice
By Bruno Rafael de Carvalho Santos•
Mar 07, 2019
a quick introduction to the basic algorithms for machine learning in R
By Mahmoud Elshiekh•
Feb 25, 2019
By Dewald Olivier•
Feb 24, 2019
great course in R, really covers the fundamentals.
By Dave Heaton•
Feb 23, 2019
This was one of my favorite courses in the specialization as it was so easy to understand and follow. I think the basis I was given has really made me want to delve deeper into the topic and apply it to my career. Thank you!!!
By Anuj Parashar•
Feb 21, 2019
This is the most interesting of all the courses in this specialization. Sometimes the content covered can be overwhelming. But the end result in the form of project assignment is worth all the efforts.
By João Freire•
Feb 14, 2019
Very good course. Clear explanations and examples give a good overview of the foundations of Machine Learning. After this course the student can build Machine Learning models.