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Practical Machine Learning on H2O, H2O

11 calificaciones
3 revisiones

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In this course, we will learn all the core techniques needed to make effective use of H2O. Even if you have no prior experience of machine learning, even if your math is weak, by the end of this course you will be able to make machine learning models using a variety of algorithms. We will be using linear models, random forest, GBMs and of course deep learning, as well as some unsupervised learning algorithms. You will also be able to evaluate your models and choose the best model to suit not just your data but the other business restraints you may be under....
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3 revisiones

por Robert H. Eubanks

Sep 11, 2018

I've taken a lot of Coursera classes and this is one of the better classes. It is a good hands-on course and will help students learn more about not only H2O, but also machine learning.

por Venkata Turlapati

Jul 01, 2018

H2O platform provides the least friction to get started with Machine Learning and Data Science for large scale data. It is very easy to setup, load and analyze data, helps in moving fast and get insights quickly. This course assumes some background knowledge in Stats, Linear Algebra, Calculus but the course work itself doesn't let you down. I would like to see more deep dive courses on various powerful algos from H2O. Thanks Coursera and H2O for offering this course.

por Marcio Gualtieri

Jun 18, 2018

That's one of those "one size fits all" attempts that end up not fitting anyone. If you don't know machine learning, you're not going to learn beyond mimicking examples of H20 code, which you could do for free by the way, using (way better) resources available on the web (H20's GitHub is a good resource). The instructor's attempts to provide intuitions on the machine learning algorithms are lazy at best. If you don't know any machine learning, you will likely get extremely confused. If you know any machine learning, you will cringe: they are just plain awful. The man didn't put much effort into this course. When things get tricky to explain, he simply excuses himself from doing it and provides Wikipedia links... Also in an attempt to reach an audience as large as possible, the instructor didn't even commit to one programming language for the course... The man goes back and forth between R and Python, half-assing both of them. He could have at least had the courtesy of providing this course's code somewhere on the web. I spent the majority of my time in this course pausing videos and typing the code from the screen... On top of everything, there are no instructors nor mentors answering to questions in the discussion forum. I took the first iteration of this course and I have seen maybe ten messages, most of them directed to the instructor and no answers whatsoever. Lastly, take in consideration that the assignments are peer-graded. I think that there is a high probability that you won't be able to get enough reviews to pass this course if you take later iterations. The number of people taking this course seem rather small.