18 de ago. de 2019
The course was well designed and delivered by all the trainers with the help of case study and great examples.
The forums and discussions were really useful and helpful while doing the assignments.
16 de oct. de 2016
Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much
por Peter F•
30 de mar. de 2020
This course would be okay if it weren't for turicreate, a Python package that's supposed to simplify things. If you have Linux or a Mac, it will do just that, but if you have Windows steer well clear of this course. The lecturers haven't considered the possibility that anyone might not have Linux or a Mac. All the faffing around getting turicreate to work (I did it once and I'm not doing it again) wasn't worth my trouble so I ended up guessing the answers to the quiz questions (you're allowed three attempts every eight hours) just to get this course out of the way. I'll use something actually accessible for the remaining courses, namely R.
por Rithik S•
26 de may. de 2020
The files that are given in readings are unable to open and turicreate cannot read that files also. I cant complete my assignments without reading those files. They haven't given any detailed explanation about how to read those files. In videos they had explained through csv files but in assignments they had given sframe file which are unable to read
por Yakubu A•
23 de dic. de 2020
The learning tools and environment is not friendly. The use of graph lab seem outdated since python 3.7 does not seem to support the module. I suggest the course be reviewed. Python 2.7 seem to be going out of the system so something should be done about this
31 de ene. de 2021
The course is limited to use special package - turicreate, sframe, no detailed explanation of how to install that. Packages used are very out dated
por Jitendra S•
29 de abr. de 2016
Dato tool does not even install properly.. so n´makes no sense to continue with the course. The support team fail to help in installing ... :-(
por Ashutosh N•
30 de may. de 2020
The course is explained using turicreate , which does not work in windows properly. It should have been explained using open source libraries.
por Krupesh A•
15 de feb. de 2019
Uses very old versions of libraries. Many students are facing issues which remains unsolved. Not recommended to pursue it.
por Shreyash N S•
20 de may. de 2020
graphlabcreate creates many problem while working..it should be changed
por Japman S•
6 de jun. de 2020
Based on Python 2 libraries not working on python 3. Obsolete Course
por YM C•
6 de sep. de 2019
Too old, bad packages, not much to learn. too basic.
por Darren R•
13 de oct. de 2015
Thoroughly disappointed to see this course based on
por Kaushik M•
1 de may. de 2016
Too many videos and not cluttered assignment codes
por D. F•
2 de feb. de 2021
Out of date material. Poor instruction
19 de abr. de 2020
This course is pretty good for beginners. All domains are explained briefly as an introduction. The best part about this course is very good hands-on sessions which are really helpful to understand concepts. The course is not very detailed but it's very good to start with. Looking forward to quality courses ahead in this specialization.
por Shibhikkiran D•
13 de abr. de 2019
This is course is very informative for a beginner. It helps you to get up and running quick provided you have little basics on Python. You should( sideline on your own interest) also pickup Statistics/Math concepts along each module to make a rewarding experience as you progress through this course.
por Diogo P•
15 de feb. de 2016
With a funny and welcoming look and feel, this course introduces machine learning through a hands-on approach, that enables the student to properly understand what ML is all about. Very nicely done!
por Karthik M•
27 de dic. de 2018
A good course to understand the basics of Machine Learning. The only issue is the use of Graphlab library. Since it only works on Python 2.7, it is not convenient for people who prefer Python 3
por Alexandru B•
21 de ene. de 2016
Great course. Very informative and inspirational. I got tons of ideas from it! Thank you
por Mallikarjuna R V•
17 de ene. de 2019
Wonderful opportunity to learn and execute hands on coding of Machine Learning. The amazing task that Machine Learning methods and algorithms does behind scene is understood for the following cases / intelligent applications:
1. Regression (e.g. Predicting House Price etc.)
2. Classification (e.g. Product review sentiment, Spam detection, Medical diagnosis etc.)
3. Clustering and Similarity (e.g. Grouping news articles)
4. Recommender (e.g. Amazon personalized product recommendations, Netflix personalized Movie recommendations etc.)
5. Deep Learning and Deep Features (e.g. Google image search, Image-based filtering etc.)
The main challenge for me was to code using “Python3, Pandas and SciKit-Learn” instead of “Python2, GraphLab Create and SFrame”. I am now confident to develop intelligent applications based on Machine Learning. Thanks to Professors (Emily and Carlos) and to Ashok Leyland-HR for giving me this opportunity.
por Sundar R•
19 de ago. de 2020
The teaching is of good quality and the lectures are easy to follow along. The only downside I thought was week 6 where I felt the topics weren't covered in enough detail in order to clear the quiz. Lastly, very disappointed by the exclusion of courses 5 and 6 which would've made this specialization a complete package.
18 de ene. de 2019
lacture was good but one point i want to share to you don't use rare tools for assignment personally i faced lots of problem while installing graphlab better to switch to some common tools like sklearn python platform .
por Yuvraj S•
1 de feb. de 2019
It is a good course if we take into account the foundational part. But since only one library has been used to solve the issues, one does not explore and write their own functions.
por Jaime R•
17 de dic. de 2018
Great introduction course. However, getting the notebooks to work with Graphlab is a real pain. The notebook exercises are also mostly make-work rather than real explorations. The explanations and the notebooks themselves are pretty good though
por Ezequiel P•
7 de nov. de 2020
Excellent Theory. Very clear explanations with simple yet powerful examples. Sadly the practical part is not nearly as good. Mainly because of the tool used. If this was implemented in Scikit-Learn, the course would be excellent overall.
por Ayush G•
5 de jun. de 2020
the course seems outdated in many aspects, the support isn't available to clarify doubts and the documentation isn't updated either. Moreover, the software support has ended.