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Learner Reviews & Feedback for Practical Machine Learning on H2O by H2O

4.5
stars
73 ratings

About the Course

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....

Top reviews

RE

Sep 10, 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.

EA

Feb 3, 2019

Great content, a lot of hands-on activities and the instructor is quite good too. By the end of the course, I feel that I have the necessary skills to work with h2o.

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1 - 17 of 17 Reviews for Practical Machine Learning on H2O

By Marcio G

•

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.

By maurizio

•

Apr 29, 2019

I follow the course but I found this problems:

1) Nobody answer the questions

2) There is no repository of the code so it is very difficult to follow the course

By Krishna T

•

Jul 1, 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.

By Robert H E

•

Sep 10, 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.

By Edwin N A

•

Feb 4, 2019

Great content, a lot of hands-on activities and the instructor is quite good too. By the end of the course, I feel that I have the necessary skills to work with h2o.

By Neil B

•

Jul 23, 2020

The course was very informative and covered a lot of important topics.

The course not only helped understand various machine learning models but also improved my programming skills.

Even the tests and peer graded assignments were not simple and direct. You had to refer to the documentations and look all over the internet.

It was a good course and I must recommend this to anyone who is interested in machine learning and data analytics.

You would not only know more about machine learning but learn how to use h2o, which is a very powerful tool that could be used in python and R.

By Miaojun Z

•

Dec 24, 2019

This course is a great introduction to H2O auto ML tool. I found it very useful in terms of showing different functions in the library, explaining the hyper parameters for fine tuning, and even some videos about data cleaning and data preparation via this tool. I will continue to practice what I have learned from this course in my projects.

By Anatoly R

•

Jan 20, 2020

The course is good. It is useful and gives you the minimum you need to work with the h2o library. But I also recommend that you study the book Practical Machine Learning with H2O by Darren Cook, which also contains additional information and examples of working with H2O.

By Robert J

•

Apr 2, 2021

Teaches one of the quickest ways to get Machine Learning through H2O's version of AutoML. You can make high accuracy models quickly and easily with H2O. Without all the fuss, you could have a prototype model in under an hour for many kinds of data.

By Felipe d J C H

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Feb 17, 2021

Es un excelente curso que te permite conocer las principales funciones de H2o, lo recomiendo ampliamente

By Mahdi P

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Aug 11, 2019

It was a great experience to work with H2O both on R as well as Python.

I learned a lot from the course.

By Kęstutis D

•

Oct 13, 2019

One of the best courses regarding machine learning!

By Francisco L M

•

Jul 30, 2021

Very practical and useful!!

By Tarkeshwar N S

•

Jul 21, 2019

great

By Yeifer R C

•

Apr 20, 2020

Is very basic and this is good for persons that they star its journey in machine learning. I recommend to do all activities in python, because is a language code most use in the market, also, is compatible with aws and google platforms.

By Rushikesh M

•

Oct 1, 2019

awsome but needs more to explain on autoencoder ,anomely

By Solomon W

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Dec 13, 2019

Very destructive format - switching between Python and R in the same video. Not good.