October 31, 2019
Score 10 out of 10
Read Abdelhalim DADOUCHE's full review
Pros and Cons
- It doesn't require you to have a Ph.D. to build models!
- You can use it to address a very large and wide dataset without worrying about sampling.
- Automation is in the product DNA. You can prepare your data, ingest it into the "Kernel", then get insights about what was found, decide to publish it and schedule scoring tasks or model refresh in the same product.
- The "User Experience" is sometimes lacking some clear basic things. Maybe a migration to a cloud-based environment will help bridge that gap.
- API is probably the next item on my list. The existing one is not easy to access or use which limits the integration capabilities.