Abstract: Abstract: MLOps has emerged as key focus area for Enterprise. But why? The answer is simple. To remain competitive in this era of digital transformation it’s become a business imperative to establish a competency around machine learning and deep learning application delivery. Now, enterprises are starting to take the next step in making the MLOps process repeatable, scalable and reproducible, so they can continuously infuse the business with innovation.
In this talk we will deep dive into 3 Enterprise case studies where leading organizations have built automated machine / deep learning pipelines, generating real business value from AI:
1. Predicting fraud at a Global Payments company
2. Serving real time recommendations for retail
3. Scaling NLP pipelines to make thousands of PDFs searchable and indexable for the organization
We’ll cover the organizational and technological aspects to consider when building up your MLOps capabilities and practical tips for success.
Bio: Delivers B2B and B2C AI/ML-based solution outcomes through Iguazio's distinctive MLOps automation technology.
Steve builts and implemented MLOps, industrial analytics and operations research-oriented software products and solutions in individual contributor and leadership roles in industries including oil and gas E&P, energy trading, derivatives trading, B2B medical, B2B high-tech manufacturing, process manufacturing, industrial goods and consulting/SI.