What is H2O AI Cloud?
H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models.
Company Details
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Real user data aggregated to summarize the product performance and customer experience.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
80 Likeliness to Recommend
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Since last award
96 Plan to Renew
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Since last award
86 Satisfaction of Cost Relative to Value
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Since last award
Emotional Footprint Overview
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+88 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love H2O AI Cloud?
Pros
- Helps Innovate
- Continually Improving Product
- Inspires Innovation
- Efficient Service
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
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Neutral
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Feature Ratings
Data Ingestion
Pre-Packaged AI/ML Services
Data Exploration and Visualization
Feature Engineering
Algorithm Recommendation
Performance and Scalability
Algorithm Diversity
Openness and Flexibility
Model Tuning
Model Monitoring and Management
Ensembling
Vendor Capability Ratings
Breadth of Features
Product Strategy and Rate of Improvement
Ease of Customization
Ease of Implementation
Business Value Created
Quality of Features
Ease of Data Integration
Usability and Intuitiveness
Ease of IT Administration
Vendor Support
Availability and Quality of Training
H2O AI Cloud Reviews
Piyush M.
- Role: Consultant
- Industry: Consulting
- Involvement: End User of Application
Submitted Nov 2024
Fantastic product
Likeliness to Recommend
What differentiates H2O AI Cloud from other similar products?
Ai featured
What is your favorite aspect of this product?
Algorithm
What do you dislike most about this product?
Not applicable
What recommendations would you give to someone considering this product?
Amazing product
Pros
- Helps Innovate
- Reliable
- Performance Enhancing
- Effective Service
Pulkit J.
- Role: Consultant
- Industry: Consulting
- Involvement: Initial Implementation
Submitted May 2024
Good product to implement ML soutions
Likeliness to Recommend
What differentiates H2O AI Cloud from other similar products?
AutoML functionality
What is your favorite aspect of this product?
AutoML with minimal code
What do you dislike most about this product?
Easy to implement without good coding knowledge
What recommendations would you give to someone considering this product?
If you are short of programmers, this is a good option
Pros
- Trustworthy
- Fair
- Client's Interest First
- Transparent
Ashay S.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Jan 2023
Best Auto-ML platform
Likeliness to Recommend
What differentiates H2O AI Cloud from other similar products?
One of the great things about it apart from the model building and deployment part is it also provides some tool access for better Interpretability and Explainability of models. It is helpful in understanding how the model works and what were the important features than contributed to getting that performance.
What is your favorite aspect of this product?
It is very fast and easy to try out multiple models on a given dataset and find the best one. It helps in hyper-parameter optimization to find best performance out of a given model , this can be monitored on the dashboard as the process is going so we needn't wait for the whole process to complete to make changes or tune it. Also the performance of the available algorithms is quite good.
What do you dislike most about this product?
There are some parts which lack good documentation and for some specific cases it lacks the algorithm support or some of the data processing steps. But unless it is a very complex case , the performance is quite good for a given task
What recommendations would you give to someone considering this product?
It has a great set of ML algorithms and support for various stages of ML pipelines that can save your time and reduce chances of error. It is quite intuitive and user friendly and doesn't require someone to be an expert in ML to use.
Pros
- Helps Innovate
- Continually Improving Product
- Enables Productivity
- Efficient Service
