Learning (ML)

Walk away realizing: -The key components of a customer insights engine -Where to start and how to prioritize customer value initiatives - a step by step approach -The challenges and best practices...

In reality, most models will be tasked with scoring unusual, anomalous, or unexpected data at some point after they are deployed.  But the more certain we are of expected conditions at the time of pre...

Our old friends at Automation Anywhere combine forces with our new friends at DataRobot to discuss the integration and convergence of RPA & Automated ML and how that combination can hurdle your enterp...

This session identifies Data Virtualization Benefits for AI & ML projects including: Reducing data exploration and analysis timeframes; Extending and integrating capabilities to improve data scientist...

How do you enable Enterprise AI transformation? Enable computation on arbitrary objects first. The complexity of possible embeddings of that computations have grown exponentially with the expansion of...

An analytically driven approach using machine learning techniques to detect misconduct and protect your enterprise.

The company sourced an AI-enabled solution to eliminate the bottleneck. Existing contracts were used to build training datasets. Clauses and terms were tagged for machine learning; the data created wa...

AI & Intelligent Automation offers global corporate enterprise executives the opportunity to re-examine attended automation through past lessons learned as well as new advancements in the technology.

Our Enterprise ML Report lays out challenges, limitations, categories and questions for you to consider as ML becomes an essential component of your enterprise.

While enterprises know they have it, putting a definition to it is a little trickier. Deepak Subbarao breaks down what unstructured data is before jumping in on this episode of “Going Hybrid.” Next, h...

A leading American bank had 35M documents automated, 150 FTE saved and 87% accuracy improved all within 2 weeks

Deepak takes us through structured data: what it is, when we need it, and when we don’t.