h2o Erfahrungen

Effective tool to gain AI insights

Vorteile:

The tool is very easy to install. Also, the interface is user-friendly. Can handle a lot of machine learning tools. Very handy tool for running quick analysis too.

Nachteile:

The documentation can be improved substantially. Also, more authority can be given to user to tweek models as per requirement.

Great at making machine learning accessible

Vorteile:

For the machine learning algorithms built into the program, they are incredibly optimizable. Every parameter and hyperparameter of each algorithm is tuneable, and the GUI allows all of this as well.

Nachteile:

Programmatically using the software is difficult because the documentation is lacking and it is hard to find the documentation that they do have. It’s easier to use the GUI, but that isn’t good for an end-to-end solution.

H2O is value use fully for artificial intelligence.

Kommentare: H2O is a Strong Performer in Predictive Analytics and Machine Learning.

Vorteile:

Mostly ai can use or automation work. and H2O.ai is a Strong Performer in Predictive Analytics and Machine Learning.

Nachteile:

In this software main part is use of that software. H2O not user friendly that way user think for uses.

Quickly build, train and tune your models

Kommentare: Almost every model I have built, firstly I give a chance to H2O and see basic outcomes. After that, I switch to Python and manually build, tune, train and test my models.

Vorteile:

I really like H2O machine learning and deep learning algorithms. I use its GUI for preprocessing and analyzing data. I can choose easily model type and tune it via options. It is really fast and run on really low memory like 2 GB. I have learn lotta new information about ML and deep learning thanks to H2O's help buttons.

Nachteile:

Some model parameters can not be changed. Also I dom't like its preprocessing process. It misreads some characters for some file types.

Mr

Kommentare: Ran analysis on the data quickly and without having to code anything.

Vorteile:

This is easy to use. I can quickly run a lot of well known algorithms without having to code anything at all. The open source nature helps too.

Nachteile:

The docume.ntation can be improved substantially. Also, need to provide the ability to tweak some algorithms.

H2O.Ai Product Review

Kommentare: The major benefit of the product in the AutoMl. It's really useful when you are trying to optimize the parameters.

Vorteile:

AutoMl is really useful and saves hours of work. H2O flow is easy use and it's very easy to get started using H2O flow. There is also support for python and R

Nachteile:

There is no feature engineering. Depending on your data size, H2O.AI can take up lots of memory.

Great Machine Learning Solution

Vorteile:

H2o Flow is one of the easiest ML solutions for beginner data scientists with the breadth and depth needed to demonstrate competency.

Nachteile:

The H2o.ai version is great (per a trial) but quite expensive and seems to be focused only on enterprises. A version for SMEs or smaller businesses would be great!

H2O Rview

Vorteile:

H2O is a powerful opensource data science and machine learning platform. Most of the ML algorithms are supported and available to use. It's easy to launch H2O from R and it noticeably increases the speed of algorithms and reduces time.

Nachteile:

It would be great if they provide more documentation and guideline.

Best place for competitive exposure

Kommentare: got exposure

Vorteile:

Truly flat organization - nobody reports to anybody else. Makers have the power to steer towards opportunities, self-organize and ship products with zero organizational barrier between the product and customers. Worth it with all the analytics

Nachteile:

lack of management and no accountability. It's hectic and unorganized to the point where you'll have no idea what you're doing, and what you should be doing.

Easy to set up and run, nice interface

Kommentare: try some ideas quickly.

Vorteile:

Notebook's nature of keeping things in one place. Some nice build-in features to interact with different data resources.

Nachteile:

Less well documented developing guideline. It's some what difficult to build something above it. Notebook has its own shortcomings, which some operations seem less convenient. For instance, if the error output is too lengthy, I have to scroll all the way up to get where I need edit the code.