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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