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Good Automl software
What do you like best about the product?
The web front end known as flow is really easy to use. It can be use to quickly create machine learning models.
What do you dislike about the product?
The complex machine learning model overfit the data. This is especially true when the data set is small.
What problems is the product solving and how is that benefiting you?
Trying to forecast prices using the regression models. It's very quick to test out new models.
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Excellent framework and application
What do you like best about the product?
Excellent support for commercial product Driverless AI. Rapid iteration. Performance is generally better than one can be achieved in code.
What do you dislike about the product?
Actually nothing. The combination of proprietary and open source tools, Driverless AI and H2O, provide tools across a full range of use cases.
What problems is the product solving and how is that benefiting you?
We work in both financial services and biological research.
Recommendations to others considering the product:
Take advantage of the 30 day trial.
Workflows for quick ML prototyping
What do you like best about the product?
They developed top-quality open source tools, including the H2O-3 and AutoML families. I do not have a license for their Driverless AI, but my experience with it through tutorials and other demos has been superb. I should mention that their efforts to develop frameworks for ML interpretability are spot on, and their learning center is shaping up as a valuable resource to the community in general. The interfaces with R and Python enable a smooth transition of pre-existing workflows into the H2O framework.
What do you dislike about the product?
Somewhat cryptic debugging msgs in H2O-3. They support specific packages for manipulating data (data.table in R, datataable in Python) for the sake of speed and big data maneuverability, although many users may find this limiting. Driverless AI may not be affordable to the small fish in the pond.
What problems is the product solving and how is that benefiting you?
I have mostly used their AutoML to build quick ML/AI prototype solutions in different domains.
Recommendations to others considering the product:
One should leverage all the resources available to test their products before buying.
h2o is my personal data scientist
What do you like best about the product?
h2o offers a well validated, fully automated, rigorous machine learning pipeline including state of the art model interpretation allowing for prediction and inferences.
What do you dislike about the product?
i have nothing dislike about h2o's products.
What problems is the product solving and how is that benefiting you?
my scientific questions involve biomedicine, neuroscience, and psychology
Accessible ML
What do you like best about the product?
Clean interface through Driverless AI and variety of analyses
What do you dislike about the product?
Better instructions would be helpful, as would clearer tutorials
What problems is the product solving and how is that benefiting you?
Need for adaptable ML analyses. Plug and play.
Its superb
What do you like best about the product?
Ease of use and its high performance for building models
What do you dislike about the product?
Does not support data cleaning and some algorithms
What problems is the product solving and how is that benefiting you?
Used to solve complex machine learning problems
Great Machine Learning Framework
What do you like best about the product?
The ability to try out multiple models with a few lines of the code is the greatest benefit
What do you dislike about the product?
H20 does a good job in abstraction of underlying transformation and tuning steps, which could be a bit challenging
What problems is the product solving and how is that benefiting you?
1. Policy Lapse Predictor - the biggest benefit is the automation of model tuning
Recommendations to others considering the product:
Great framework
Great ML framework
What do you like best about the product?
This is a cross-platform, integrated framework for ML that is continuing to evolve with topics important to data scientists.
What do you dislike about the product?
Developing support for a wide range of NLP preprocessing
What problems is the product solving and how is that benefiting you?
Problems in academic research and healthcare
Great Product
What do you like best about the product?
The best part of H2O.ai is its ease of use and seamless UI.
What do you dislike about the product?
One downside of H2O.ai is, as with many services, its bugs which do not return human-readable debugging statements.
What problems is the product solving and how is that benefiting you?
I have used H2O for time-series data, and stock market prediction.
A very good experience with Machine Learning
What do you like best about the product?
AutoML is a great product. They have other ones, but AutoML is the most impressive.
What do you dislike about the product?
Nothing, maybe the integration with Spark could be improved but only in little details.
What problems is the product solving and how is that benefiting you?
Forecasting models and finding for best algorithms for my datasets
Recommendations to others considering the product:
It's an amazing set of tools, easing the use of machine learning and giving a lot of advances to write & discover models.
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