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.
Good Customer support
What do you like best about the product?
Being a user I really enjoyed the support and dedication that team shown to help us is really great!
What do you dislike about the product?
H2O should stay ahead of the curve to give support to new technology stacks like databricks.
What problems is the product solving and how is that benefiting you?
We use H2O for our model building
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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.
H2O.ai is a great tool who wants to build a scalable and interpretable machine learning pipeline.
What do you like best about the product?
I find it most helpful that it provides GUI for users to estimate how long the model will run as well as the water meter showing how the resources are used along the modeling process.
What do you dislike about the product?
H2O Frames have very limited data processing options compared to python pandas or pyspark dataframes. If we can have more data maneuverability, I think it would help a lot.
What problems is the product solving and how is that benefiting you?
Purchase forecasting, employee estimation, etc.
Recommendations to others considering the product:
I believe it is a great tool for those who are looking to establish ML pipeline with ease.
Driverless AI application for Auomated Machine Learning and Data Analytics
What do you like best about the product?
Easy to use with good UI design and automated ML function. Driverless AI has strong capability on the auto feature engineering and system visualization. The auto feature engineering has supported different machine learning algorithm (Random Forest, Decision Tree, Neural Network, Deep Learning, etc.) and feature parameter tuning (accuracy, time, system computing etc.) The system also helps user to reduce time and efforts for hyparemeter tuning and compare the model with different settings. This will optimize the process and provide the most efficient model for prediction in classification or regression domain. Besides, Driverless AI also has good UI design and visualization. The UI also supports end user to quickly import data, visualize data in different categories, as well as check on the system running and performance during the Auto ML process. The end user could also observe experiment summary and accuracy matrix, as well as model comparison in term of accuracy.
In addition, Driverless AI also supports the AI Interpretation to explain on the model and performance. This function is very helpful to end user for understanding the Machine Learning blackbox, as well as management team for decision making based on extensive information.
In addition, Driverless AI also supports the AI Interpretation to explain on the model and performance. This function is very helpful to end user for understanding the Machine Learning blackbox, as well as management team for decision making based on extensive information.
What do you dislike about the product?
It is great if Driverless AI could support deployment for edge computing, which is common in IoT world. The edge computing will require efficient computing and good accuracy with AutoML algorithm. This will help much the customer for deployment.
What problems is the product solving and how is that benefiting you?
Data analytics for predictive maintenance. It could make easy-to-use for system operator.
Recommendations to others considering the product:
Yes, H2O.ai DriverlessAI is a good AutoML platform for company, which does not have Data Scientist.
Excellent software - great addition to a data science team
What do you like best about the product?
Excellent support. Useful and reliable software. Easy to deploy.
What do you dislike about the product?
No issues. The software works very well.
What problems is the product solving and how is that benefiting you?
Predictive analytics in credit and marketing. Software works well in our systems.
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.
Excellent machine learning tools
What do you like best about the product?
Good integration between development and production. Simple and powerful visual interface to complex backend. Very rapid iteration of products, continuous improvement.
What do you dislike about the product?
Price is high for closed source product, Driverless AI. It's worth it if you have a serious application, but the cost is an impediment to early adoption.
What problems is the product solving and how is that benefiting you?
Streamlining our process for generating and deploying machine learning models.
DriverlessAI
What do you like best about the product?
H2O provides DriverlessAI for an efficient AutoML platform and effective UI tools for data scientist and end-user.
What do you dislike about the product?
DriverlessAI could provide more use-cases in Manufacturing domain.
What problems is the product solving and how is that benefiting you?
We are working on Predictive Maintenance and Analytics, which could be potentially used for Manufacturing and Factory.
Great AI product
What do you like best about the product?
Many model types, great cluster performance, easy to setup
What do you dislike about the product?
Would like to see SVM , Gaussian processes, and some time series models
What problems is the product solving and how is that benefiting you?
AdTech modeling. Can create complex models on data sets with a billion rows. Much faster turnaround time
The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm, but the interpretability module has room for improvement
Our primary use case is machine learning.
How has it helped my organization?
It has enabled our work force to be more efficient.
What is most valuable?
One of the most interesting features of the product is their driverless component. The driverless component allows you to test several different algorithms along with navigating you through choosing the best algorithm. It also gives you an interpretability capability which allows you to have some understanding of what's inside the algorithm and why it's behaving a certain way, making sure you are not bias towards the outcome.
What needs improvement?
The interpretability module has room for improvement. Also, it needs to improve its ability to integrate with other systems, like SageMaker, and the overall integration capability.
I would like more support for scalability and deep learning. Right now, they are very strong in supervise and supervise learning, but not in deep learning. I'd like to see them be more well-rounded, where they have support for deep learning, but I'm not sure that is their business model.
For how long have I used the solution?
One to three years.
What do I think about the stability of the solution?
In terms of the stress we put on it, it is still in the very early days for us to actually take it through its phases.
What do I think about the scalability of the solution?
It does appear to scale. We have very large use cases. The product scales as advertised.
How is customer service and technical support?
They have excellent tech support.
How was the initial setup?
It was fairly easy to set up, then get up and running.
Which other solutions did I evaluate?
It was already selected. I don't know what process the company went through.
What other advice do I have?
Do your due diligence, making sure with your use cases, this is the right product for you.
Directionally, they are headed in the right place. They're also putting a lot of muscle behind it, but they're very focused in one area. Supervised on supervised learning is the market that they're going after. If that's their strategy, then they'll get some part of the market, but they'll leave the other part of the market behind.
We use just the AWS version of the product.
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