Software Engineering Institute

We are in the era of the Intelligent Web where machines interact with machines. We see that Machine Learning is being widely used in every field due to the revolution in cloud, computing and memory. That has created an urgent need to secure the data exchanged between the various intelligent machines to ensure that we obtain secure and reliable predictions and prescriptions. This is where we need to embed security into Machine Learning, and this is where DevOps can drive security for Machine Learning. We’ll share learnings on the importance of shift-left testing in real-time to secure and audit ML models in production.

Watch the video on YouTube.