Jan 17, 2017
Excellent course, well thought out lectures and problem sets. The programming assignments offer an appropriate amount of guidance that allows the students to work through the material on their own.
Aug 25, 2016
excellent material! It would be nice, however, to mention some reading material, books or articles, for those interested in the details and the theories behind the concepts presented in the course.
By Ernie M•
Sep 25, 2017
I enrolled in this specialization to learn machine learning using GraphLab Create. Half way into the specialization the creators sold Turi, GrapLab's parent company, making it non available to the general public (not even by paying) and then all the knowledge devalued. I wish I had known this and I would have enrolled on a different specialization. The creators still give you the possibility of using numpy, scikit learn and pandas but I had already done a lot with GraphLab create. The time I invested on my nights after work became a waste. I was trying to convince the company I worked for to buy licenses for GraphLab create.
Coursera should not allow folks to create courses that promote a private license course because it would make people waste their time and money if they decide to privatize the software.
Don't take this course, and if you take it then only use GraphLab create when the authors give you no other option.
Teaching style: Carlos was good, Emily is not very clear and loses focus of the topics and often rambles. She seems very knowledgeable but she lacks clarity of exposition when compared to Carlos or Andrew Ng.
By Tsz W K•
May 15, 2017
The materials presented are excellent with well prepared skeleton codes for all ML models. Comparing this course to its three preceding ones, this course is more challenging both conceptually and computationally. The slight drawback is that, because of the highly technical nature of the last three weeks' materials, there isn't enough guidance about how one may construct the ML algorithms from scratch, that is, learners with less experience in computing will, more or less, have to accept the sample codes with little confidence about how to (re)write such codes in the first place.
As a result, I believe that learners with more experience in algorithms and data structure (or learners who proceed to learn more about this area) are likely to gain more from this course for at least two reasons: i) they are more comfortable with the complicated ML algorithms; ii) they can improve the algorithms to speed up the estimation time (some advanced techniques are quite computationally expensive, say over 20 minutes).
In general, I have learnt very much from this course and love it.
By Eugene K•
Feb 10, 2017
If you are considering this specialization I would recommend the Andrew Ng course instead and the main reason is that it isn't depend on proprietary ML framework. Despite the good lectures, the assignments don't help you develop the knowledge required for ML developer role.
Taking in consideration the permanent postponing the courses delivery, from summer 2016 to summer 2017, finally the most interesting part of the specialization was cancelled. I'm completely disappointed with the specialization learning expirience.
By Dimitrios Z•
Jun 08, 2019
It has intresting theory but I believe the exercises need to be improvised. Maybe using Jupyter online and guiding the student to write code to solve the problems. In conclusion, I understood the basic theory but mostly that.
By Dohyoung C•
Jun 04, 2019
LDA is little bit difficult to understand, but K-mean and Mixture models are easy to understand and quite important for clustering..
By YASHKUMAR R T•
May 31, 2019
Awesome course to understand the concept behind Gaussian Mixture model.
By Dennis S•
May 19, 2019
Amazing course. The Instructors did an awesome job of preparing and presenting the material.
I think there is no better and more approachable in-depth course out there. Thank you so much!
By Jafed E•
May 14, 2019
Able to concentrate and stay focused for periods of several hours, even when tasks are relatively mundane, and doesn't make mistakes. He has a high boredom threshold. Always assured and confident in demeanour and presentation of ideas without being aggressively over-confident. No absences without valid reason in 6 months. Reaches a decision rapidly after taking account of all likely outcomes and estimating the route most likely to bring success. The decisions almost always turn out to be good ones.
This Course always completes any assignment on time and to a high standard. This Course has outstanding artistic or craft skills, bringing creativity and originality to the task. Aiming for a top job in the organization. He sets very high standards, aware that this will bring attention and promotion. This Course pays great attention to detail. He always presented work properly checked and completely free of error.
By kripa s•
Apr 30, 2019
One of the best training experience...
By Martin B•
Apr 11, 2019
Greatly enjoyed it. As with the other courses in this specialization the discussion of the subjects is impeccable, especially if you've taken some preparatory mathematics courses. The reliance on Graphlab Create is a drag though.
By Akash G•
Mar 11, 2019
Machine Learning: Clustering & Retrieval good and learn easily
By Sathiraju E•
Mar 03, 2019
Very nice course. Things are well explained, however some concepts could be expanded more.
By Jialie ( Y•
Feb 21, 2019
The course is really helpful, though it would be better for teacher to illustrate the concepts by using examples, instead of abstract terminologies
By Edwin P•
Feb 15, 2019
Excellent, good contribution to the technical and practical knowledge ML
By Zhongkai M•
Feb 12, 2019
Great assignments : )
By Vikash S N•
Feb 03, 2019
It was great but I was also interested to implement the solutions with pyspark...though I did it eventually. Thank you!
By Srinivas C•
Jan 07, 2019
This was a really good course, It made me familiar with many tools and techniques used in ML. With this in hand I will be able to go out there and explore and understand things much better.
By Jay K S•
Jan 05, 2019
Excellent course material and fantastic delivery. You guys made this complex learning so simple and interesting . Thanks for all this, keep the good works.
By KAI N•
Jan 03, 2019
Excellent course with great and reachable explanation
By PRAVEEN R U•
Dec 27, 2018
Nice content and well made presentations.
By Big O•
Dec 21, 2018
More detail on theory behind LDA and HMMs would have been useful. Otherwise, another brilliant course!
Dec 19, 2018
Great but hard~!
By Martin R•
Dec 12, 2018
I'd bring the last summary video at the beginning (the great summary of all weeks of the course). This would outline the course evolution in advance and give guidance what's ahead. IMHO this would help to not get lost when drill down in a single section.
By Manoj K•
Nov 26, 2018
session was very helpful & full with relevant contents
By Somu P•
Nov 17, 2018
Excellent course, which gives you all you need to learn about machine learning. Concepts and hands on practical ex