Deploying Models Coverted to ONNX Format

The article explains how developers can deploy machine learning models that have been converted to the ONNX (Open Neural Network Exchange) format, which is an open-source standard for representing models from frameworks like PyTorch and TensorFlow. It highlights the benefits of ONNX such as improved cross-platform compatibility, performance optimizations, and interoperability and outlines basic steps for converting models and deploying them using ONNX runtime and deployment tools.

Supported Foundation Models In Watsonx.AI

IBM watsonx.ai offers various foundation models for generative AI, including IBM‑curated, custom, and prompt‑tuned models. They can be deployed on shared or dedicated hardware, with billing based on usage (tokens or hours).

py2eviews: Python + EViews

The purpose of the py2eviews package is to make it easier for EViews and Python to talk to each other, so Python programmers can use the econometric engine of EViews directly from Python.