The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.
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
von Jesse G•
"Breadth with Depth!" That's what you'll get from taking this course (quoted because those are the words used to describe the general education pattern at my university). I never used the forums for this course and had to learn software than what I'm used to working with (sci-kit). When stuff worked it was rewarding, but other than that, expect to read documentation if you get stuck. Finally, for anyone who want to know what Machine Learning is about, this courses is the sampler of what is to come in later courses.
von Christopher A•
I really liked the case study approach to the topic. The instructors' approach to teaching through the Python notebook made it easy to follow and see things implemented as you learned them. In addition, they presented the material at a good level - not too general not too detailed for an intro taste to the topic. The professors were engaging lecturers as well and I found myself quickly going through each week's content to get to the the enjoyable assignments. I'm excited for the other courses in the Specialization.
von Anshul S•
its a very good introduction to machine learning ,although this course is little bit outdated for eg: graphlab is now turicreate and some functions of graphlab doesn't work on turicreate so you have to search the appropriate functions and for handling data they use SFrame which I hate, pandas is much better. but this course is not about what framework they are using its about learning the algorithms that makes machine learning possible and in that case both the instructor did a fabulous job
von Rahul R•
This course is awesome. One of the best course available in Coursera platform. I really appreciate both instructors' hard-work. They are fun loving and enjoy teaching; at the same time they understand, how to make student listen and understand concepts. Both the instructors are really really awesome and genius as they explains every complex concept with simple explanation. Both of them reminds a quote by Albert Einstein -“The definition of genius is taking the complex and making it simple.”
von Mariano C F d L•
The best online class I ever took. It covers a lot of basic ML algorithms and concepts (with no explanation of details), so you get a nice overview of how this field works and you can move on from there to see what is better for you. I have used the website videos many times to remember what we cover. It also gives you a good exposure to Python. the case study approach is better for understanding the material. I will definitely recommend this class to anyone how wants to know about ML.
von Mayur J•
I am really liking this course as the instructors are teaching the concept just not theoretically but building a foundation by practical samples and assignement.
The course series is well designed, firstly by this course you get feel of what machine learning is and where all you can apply the concepts. Starting with all the types of ML concepts instructors are building interest among the students.
I would recommend this course to all serious students who want to get into the world of ML.
von Целых Л А•
It was a really rewarding course! Although I participate with my colleagues and partners in the development of decision-making methods based on a completely different approach, this course was useful for me to reflect on my own scientific position and to increase my competence in achieving my scientific goals. Although, apparently, the main goals for all of us are the same. The teachers were very charismatic! Course - available for understanding and implementation. Thank you so much!
von Jun Q•
I am Jun Qi, a Ph.D. student in the department of Electrical Engineering at University of Washington. I ever took Carlo's excellent machine learning courses at UW and was really feeling pretty good. Although I may become an intermidiate machine learning researcher, I am of great interest in taking his new on-line courses because his new courses are more pracitcal and focus on large-scale data processing. So I highly recommend Prof. Carlos's machine learning courses on the Coursera.
von Kevin Z•
Two things make me follow this specialization.
Firstly, the Final Capstone mentioned in this course excites me for it is more likely to build a product rather than just to understand some concepts from doing a little programming assignments
Secondly, these techniques are very useful and cool.
But I think this specialization lasts too long and two weeks' material could be done within one week. It is more helpful if other courses in this series would be opened as soon as possible.
von Iñaki D R•
Uno de los mejores cursos para poder entender y practicar en un nivel principiante las principales técnicas de machine learning. Los profesores son excelentes en sus explicaciones y mantienen un gran interés en la clase y sus actividades. Las evaluaciones son objetivas y siempre te brindan el material de apoyo necesario para poder realizarlas. Estoy muy animado de haber cursado este curso y lo considero con la preparación suficiente para tomar los cursos que le siguen.
von Usman I•
For me, this course excelled at brushing up ML concepts I had studied years ago and clarifying the appropriateness of different techniques for different problem settings. However, the best part about this course, and the reason I took it in the first place, was that it introduces participants to a new tool that is scalable for use in larger / production systems.
I am much obliged to the instructors and am sure to continue on to the next course in this specialization.
von Bayardo E Q T•
First of all, sorry for my English. The course is a very interesting first experience with the machine learning and give a base by
all the panorama, the class are funny and easy to understand, and the professors are excellent with the explanation. I really recommend this course for all the people that be start with this new world that is the ML.
Pd. by the way, for the people that no speak a very well English, don't worry, is easily to understand both professors.
von Leonardo M O•
Amazing course. I had already done other ML Courses at coursera, but the competitive differential is the friendly approach took by the professors. Carlos and the other girl are very nice, they smile...so the training gets less formal, they look like a friend telling stories in a bar. Another main point is really the uses cases. They swap between the big forest map and the detailed view of the leaf in a succinct way. Easy to understand both views. Congratulations.
von Himadri M•
The Course literally boosts off one's confidence in ML, and gives one the confidence to proceed to higher levels in ML.
Great Course, Superb Instructors and Excellent Course material ! The complete ingredient for a perfect starter course !
I would like to mention that i came to know how to write a review using the words: Great , Good , Superb and Excellent , so that my review is rated above others by the algorithm !
So thanks Carlos sir for this superb course ! :D
von Gurmeet S G•
A good start to ML. Light on the programming / algorithms but that helps focus on the concepts which is appropriate for a complete beginner to ML.
It took a while to get set up because of the Python and turicreate versions for Mac OSX so I almost dropped out of this course. Glad I kept to it though. Maybe more value in using the standard packages to make skills comparable to others, but I appreciate that turicreate has been optimised for large datasets.
von Abhijit D•
Excellent course presentation by Emily and Carlos - If courses are presented in this interactive manner learning will always be fun and interesting.
Always advisable to have some basics on python , data frame , machine learning(if possible) and you will go really smooth with this intermediate level course.
Course material really good for machine learning with real case studies and capstone project on deep learning was indeed the crown of the course.
von Louis U•
Absolutely awesome! I am really appreciative of the time and efforts on the part of the instructors and the University of Washington to make Machine Learning very accessible. The concepts were very easy to grasp and I endorse the case study approach as a effective introduction to complex topics. Obviously, it will get more detailed and complex in upcoming courses in the specializations but I feel very prepared and excited to learn. Thank you.
von Syed M Z H K•
Thanks alot for this awesome course. As because of it, I was able to learn python (otherwise I used to hate it, when I started learning it with OpenCV) and ipyhon (which is an awesome tool). Furthermore, thanks alot course era for providing me with this amazing fee waiver (since I can't afford this course) , as because of this I am hoping to excel in this field after completing this specialization, in order to later land good job. Thank you!
von Prachur B•
A very practical approach for learning and get excited about Machine Learning. The python notebook exercises really help if you do them diligently (though sometimes it was too easy because of hints, may be hide them and who when someone asks for it). The mention of so many concepts and algorithms can be overwhelming, so a clear guideline on how to leverage the material specifically in this foundation course in the closing remarks would help.
von Aman M•
I was totally new to the machine learning, but this course helped me to understand what is it? What is the importance of it ? where it can be used and what will be the future of it ? There was also enough exercise work to check our understanding to the topic learnt. I think it will be more interesting if they provide a console for code snippet for the assignment... It was very nice experience with Carlos Guestrin Sir and Emily Fox Ma'am
von Tobi L•
I appreciate that the first course focused on applications, I've got plenty of math and programming experience, but I took this specialization to really grok machine learning and its applications. By using graphlab as a black box and focusing on specific applications, I really understood why these techniques are useful. Once I've got the why, I feel much more motivated to dig deeper into the how, which I feel confident enough that I can do.
von Aleksander S•
This is a great course. The content is delivered at a very good pace even for people with little prior knowledge of statistics or computer science — not too fast (would be too difficult) and not too slow (could become boring). Additionally, the assignment model is perfect — it requires completing hands-on exercises, but then the solution is assessed using simple quizzes. Thanks to that the answers and the grades are immediately available.
von George C•
The case study approach and the reliance on GraphLab library makes it easier to get your head around the concepts before going into the detail later in the specialization. I learn better when I have a working understanding of the high-level concepts and the use for a new area of study. This course provides that high-level understanding and the later specializations provides the deep dive. Also, the course seemed well paced and structured.
von Chengcheng L•
This is a wonderful course to get you into the door of machine learning. It covers several key concepts in ML. The videos are easy to follow. The assignments are not difficult to complete if you do the "follow along" exercises. You won't be able to understand the theoretical background of the algorithm very well after taking this course, but you can apply Grahphlab functions to whatever data you have and generate quick and dirty results.
von Evan S•
This course was a great balance between lecture (and lecture quiz) & iPython lecture (and iPython lecture quiz). I like that the answers are multiple choice as opposed to copying and pasting code. That way, any coding errors can be played around with in the notebook first without using up any submission attempts. Emily and Carlos did a great job of keeping the course fun while sticking to the easy-to-understand case-study approach.