H2O Artificial Intelligence
H2O.ai | 1.0Linux/Unix, Other 20170411 - 64-bit Amazon Machine Image (AMI)
External reviews
External reviews are not included in the AWS star rating for the product.
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.
- Leave a Comment |
- Mark review as helpful
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.
Good and easy
What do you like best about the product?
Streamlining our process for generating and deploying machine learning models.
What do you dislike about the product?
it its not much friendly when you try to automatize process
What problems is the product solving and how is that benefiting you?
machine learning models
Recommendations to others considering the product:
Streamlining our process for generating and deploying machine learning models.
Expanding AI Product with Excellent Support
What do you like best about the product?
The predictive modeling and machine learning capabilities of this product are top-notch along with their support and training.
What do you dislike about the product?
Documentation in general can be improved.
What problems is the product solving and how is that benefiting you?
We have been able to create features previously undetected and build more accurate prediction models.
Recommendations to others considering the product:
Ask for H2O's training before you use the software - you'll have a much better time.
It is helpful, intuitive, and easy to use. The learning curve is not too steep.
Our primary use case is for data science. Some of our data scientists use it pretty heavily to build models.
How has it helped my organization?
One example, we are able to automate life insurance. We have to underwrite policies. When somebody applies for a policy, we take their blood, then assign them a risk: substandard, standard, preferred, etc. Depending on this, we price our products. Usually the process is that you take the blood, then it goes to a lab and we get the lab results back, then an underwriter takes a look at the lab results. This is usually done in a two week time frame to get a rating. We were able to build models to automate all of this, and now, it happens in real-time. Somebody can apply online and get issued a policy right away.
What is most valuable?
It is helpful, intuitive, and easy to use. The learning curve is not too steep.
What needs improvement?
The model management features could be improved.
For how long have I used the solution?
Three to five years.
What do I think about the stability of the solution?
We haven't put a lot of stress on it.
What do I think about the scalability of the solution?
The size of the environment for my database is probably about 900TB.
So far, the product has been good from a scalability prospective.
How is customer service and technical support?
I would rate the technical support as an eight out of ten.
How was the initial setup?
The integration and configuration were good. I would rate them as an eight out of ten.
What was our ROI?
We have seen significant ROI where we were able to use the product in certain key projects and could automate a lot of processes. We were even able to reduce staff.
Which other solutions did I evaluate?
We looked at Amazon SageMaker on AWS.
This product still was open source at that point, then we did get proprietary support after that. The other products were not open source, and we couldn't really try them out beforehand to see if we liked them or not.
H2O.ai is a great product for data scientists in general. It has a lot of options and is really flexible. Also, the pricing was good.
What other advice do I have?
H2O.ai works directly with a lot of our cloud data, big data environment, and Amazon RedShift environment. The big data integration was easier from a performance perspective than Amazon RedShift. That is because our big data environment is still on-premise vs RedShift, which is on the cloud, so we had to go through some struggles to get it operating with RedShift.
Popular machine learning platform
What do you like best about the product?
I met h2o.ai with Gartner Magic Quadrant. It's great ML platform with it's extensive built-in library.
What do you dislike about the product?
Price architecture is confusing a bit. Also we'd like to see more use cases and customer stories for marketing applications.
What problems is the product solving and how is that benefiting you?
We evaluated churn prediction algorithms to score our customer database.
Very easy to use
What do you like best about the product?
the tool itself is very intuitive and easy to use.
installation is quick.
porting to R and Python options are nice to haves.
installation is quick.
porting to R and Python options are nice to haves.
What do you dislike about the product?
there isn't much visibility into how h2o is better in using each algorithm.
What problems is the product solving and how is that benefiting you?
machine learning. expediting the process and replicating the process.
showing 1 - 7