TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

Machine learning predictions and system updates in real-time. Huyen's analysis refers to real-time machine learning models and systems on 2 levels. ... and these frameworks are not Python-native, ...

Since DJL is machine learning framework-agnostic, the engineering team doesn’t need to make code changes in the future if the scientists want to migrate their model to a different ML framework ...

For models trained on tabular data, we adopt SHapley Additive exPlanations local explanations to gauge how each patient feature contributes to the predicted outcome. We explain graph machine learning ...

Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.

NIMS and its collaborators have developed a model designed to predict the long-term durability of a range of heat-resistant steel materials by performing machine learning while preserving the ...

Data Prep for Machine Learning: Encoding. Dr. James McCaffrey of Microsoft Research uses a full code program and screenshots to explain how to programmatically encode categorical data for use with a ...

This article explores what knowledge graphs are, why they are becoming a favourable data storage format, and discusses their potential to improve artificial intelligence and machine learning ...