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Scale your ML and AI with Production-Sized Models
By Yotam Kramer
See how data scientists can run their data preparations and machine learning ops even faster using SQream’s connector to Jupyter Notebook Python and TensorFlow.
Massive data is the key to successful AI/ML. The more data used in the training, testing, and validation phases, the more accurate and significant the results. Yet most enterprise data scientists are able to utilize only a small portion of their exponentially growing data.
This example was done using SQream Python connector, learn more here
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