Aug 14, 2020
recommended for all the 21st centuary students who might be intrested to play with data in future or some kind of work related to make predictions systemically must have good knowledge of this course
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.
par David S•
Feb 07, 2016
The course gives a clear explanation of why machine learning, with a goal of prediction, is different from regression. The use of the caret package in R is emphasized. Caret provides a uniform interface to many different machine learning algorithms, leaving no excuse for practitioners not to test a variety of approaches to confirm the robustness of their conclusions.
par Tai C M•
Sep 29, 2017
This is my favourite course in the data science. Prior to taking up this course, I have been using technical analysis to achieve my investment goal. I know how to design trading system to trade. Now with machine learning, I learned something new. System trading is reactive and machine learning is predictive. This subject is the reason why I sign up for data science.
par Jose A R N•
Dec 08, 2016
My name is Jose Antonio. I am looking for a new Data Scientist career ( https://www.linkedin.com/in/joseantonio11)
I did this course to get new knowledge about Data Science and better understand the technology and your practical applications.
The course was excellent and the classes well taught by the Teachers.
Congratulations to Coursera team and Teachers.
par Triston C•
May 27, 2017
This course really demystified machine learning, and provided practical steps and guidance on how to create predictive models. While I do wish there were more resources on how to tune models and investigate specific model parameters, I understand that there just wasn't enough time. I couldn't imagine a better course for a solid foundation in this skill.
par Edward R•
Dec 17, 2017
Great course, but it may take you more than the allotted 4 weeks if you intend to dig a bit deeper and pursue some of the additional resources referenced throughout the course. I would definitely recommend doing that, as there is A LOT of material to cover if you, like me, just have to know the details of what's happening behind the scenes.
par Rebecca K•
Sep 24, 2018
This course gave a great basic understanding of some different machine learning algorithms and what they do. I now have a great practical understanding of how to implement them, and enough understanding of theory to know what I'm talking about and to be able to learn more about them in the future.
par Nirav D•
Apr 02, 2016
This is a very useful course in Machine Learning that teaches us how to use the R based packages such as CARET for applying machine learning techniques. The course project helps understand how these techniques are applied in real world applications and develop useful insights.
par HIN-WENG W•
Feb 07, 2017
PML is a deep subject and this course is an excellent foundation for further studies. Prof Leek has taught brilliantly on the basic concepts of PML given the short time of 4 weeks. You need college level statistics to fully appreciate the theories of the PML's lectures.
par Raja F Z•
Apr 13, 2020
It is a well designed course, for academician as well as practitioners. Syllabus of the course, covers a lot of algorithms. Course content, presentation, assignments are very practical and give a lot of knowledge, understanding and practical tips..
par Rishabh J•
Aug 22, 2017
All the major machine learning algorithms and techniques are provided in a way that you can begin using them right away. The course project also provides an opportunity to apply the different techniques learnt in class to a rather messy dataset.
par Nino P•
May 24, 2019
It's good that they teach you basics of machine learing in R (caret package), but it's very introductory course. I definetly recommend this course to beginner, but I also recommend taking more courses on this topic (Andrew Ng's for example).
par Paula L•
Dec 02, 2016
good course, but one who is serious about data science should view this course as a starting point since machine learning is a semester long course so I'd recommend follow up with machine learning course taught from Andrew Ng out of Stanford
par Bill K•
Feb 10, 2016
Really good class. I think there were some small issues with the class project. Like all real world problems it was not entirely well specified and the data was a bit odd to use for a prediction exercise because it was time series data.
par Stephanie D•
May 21, 2017
This was definitely a challenging course. I learned a lot about building and testing prediction algorithms. The course also helped me overcome the feeling of intimidation by providing excellent examples and a hands-on final assignment.
par Yusuf E•
Oct 17, 2018
It would have been nice if there was an introduction to deep learning. Also, linear methods are discussed at length again which is not really necessary. Otherwise, great course to get you started on machine learning applications in R.
par Athanasios S•
Aug 09, 2018
Great class! I wish you would do a little more explanation about what methods are best for which scenarios. If you did in fact explain that and it went over my head or I missed it, I apologize. Great class that I learned a lot from.
par Dave H•
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!!!
par Pei-Pei L•
Jul 27, 2017
This course covers a lot of information in a short time, but you'll feel very proud of yourself when you finish it! It made me feel much more comfortable with writing machine learning programs, and am ready for the next topic!
par Kristin A•
Jan 09, 2018
Good intro to a topic that has a lot of power and a rich body of knowledge behind it. You can only scratch the surface in a four-week course, but I have been exposed to quite a range of tools in Practical Machine Learning.
par Samuel H•
Feb 18, 2016
This was a very good introduction to machine learning and how to use machine learning packages in R. It would have been better if the class had been longer than four weeks, but I learned a lot for the length of the course.
par Mohammad A•
Jan 17, 2019
Wonderful course and instructor, it was the best in the specialization courses so far.
One note is that for most of the methods the explanation was too much precise and short and needed to reinforce it by extra material
par manny d•
Sep 10, 2017
Best course i have ever taken on Machine Learning! Excellent presentation and excellent reference sources. Machine Learning is not that hard as I thought it would be..please make more practical courses like this one.
par ARVIND K S•
May 24, 2020
It 's a great machine learning course for beginners as well as students with experience. The quizzes and peer assignments are invaluable and if done with a purpose can augment knowledge of the subject immensely.
Dec 13, 2016
Awesome course. Jeff Leek does a truly amazing job at explaining very complicated concepts thoroughly and quickly. I'm surprised we went through as much material as we did. Out of the 9, this is one my favorites.
par Adam R•
Nov 11, 2018
Best course in the data science series. It is practical, so if you are looking for something theoretical this will not be the course for you. Also good introduction the methods for model testing and validation.