Business case, meet applied machine learning
Companies that effectively apply machine learning can drive efficiency through automation and create new business opportunities. We know, because our customers are doing it:
- A bank is creating 80% of its compliance documentation through natural language generation
- An accounting firm is using summarization techniques to reissue guidance to customers when a tax law changes
- A hospital is using deep learning image analysis to improve surgical procedures through robotics
And that’s just the tip of the iceberg.
Our latest report and prototype shows how to make models interpretable without sacrificing their capabilities or accuracy.
Here, we show how to use probabilistic programming and Bayesian inference to easily build tools that make better predictions for more effective decision making.
Learn how to use deep learning and embeddings to make text computable for a variety of business applications and products.
Deep learning: Image analysis
This report explores the history and current state of deep learning, explains how to apply it, and predicts future developments.
Probabilistic methods for realtime streams
Here, we explore probabilistic methods that offer highly efficient models for extracting value from streams of data as they are generated.
Natural language generation
In this report, we look at how machine systems can turn highly structured data into human language narrative.
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