Executing ML Services Scripts From Jupyter Notebooks

Kevin Feasel

2018-07-17

Python

Kyle Weller has an inception moment with Python and SQL Server Machine Learning Services:

While this example is trivial with the Iris dataset, imagine the additional scale, performance, and security capabilities that you now unlocked. You can use any of the latest open source R/Python packages to build Deep Learning and AI applications on large amounts of data in SQL Server. We also offer leading edge, high-performance algorithms in Microsoft’s RevoScaleR and RevoScalePy APIs. Using these with the latest innovations in the open source world allows you to bring unparalleled selection, performance, and scale to your applications.

Normally I see examples come straight from SQL Server or maybe C#, but it’s a bit fun to see one originate in Python on order to execute Python in SQL Server.

Related Posts

A Quick Keras Example

Shubham Dangare takes us through a quick example using Keras and TensorFlow in Python: Keras is a high-level neural networks API, written in Python and capable of running on top of Tensorflow, CNTK  or Theano. It was developed with a focus on enabling fast experimentation. In this blog, we are going to cover one small […]

Read More

ML Services and Injectable Code

Grant Fritchey looks at sp_execute_external_script for potential SQL injection vulnerabilities: The sharp eyed will see that the data set is defined by SQL. So, does that suffer from injection attacks? Short answer is no. If there was more than one result set within the Python code, it’s going to error out. So you’re protected there. […]

Read More

Categories

July 2018
MTWTFSS
« Jun Aug »
 1
2345678
9101112131415
16171819202122
23242526272829
3031