GitHub

Debugging Machine Learning Models with Python

What is this book about? Debugging Machine Learning Models with Python is a comprehensive guide that navigates you through the entire spectrum of mastering machine learning, from foundational concepts ...
SiliconANGLE

Microsoft releases TensorWatch, a tool for visualizing and debugging AI models

A month after releasing the code for one of the core algorithms behind Bing, Microsoft Corp. today made another notable contribution to the open-source community. The company’s research division today ...
EDN

‘OnDemand’ models speed firmware debugging

Striving to meet the demands of firmware developers, Carbon Design Systems announced Wednesday (May 16) a new technology called “OnDemand” that speeds the performance of Carbon's Virtual System ...
VentureBeat

Uber open-sources Manifold, a visual tool for debugging AI models

Debugging machine learning (ML) models isn’t a walk in the woods. Just ask the data scientists and engineers at Uber, some of whom have the unenviable task of digging into algorithms to diagnose the ...
IEEE

Prompt Engineering for Python Code Debugging with Large Language Models: A Comparative Analysis of Zero-Shot, Few-Shot, and Chain-of-Thought Approaches

Abstract: This paper presents a comprehensive comparative analysis of three distinct prompt engineering strategies—Zero-Shot, Few-Shot, and Chain-of-Thought—for Python code debugging applications ...
GitHub

leeroopedia/workflow-onnx-onnx-reference-evaluation

This workflow provides a structured process for executing ONNX models through the ReferenceEvaluator — a pure Python implementation of every ONNX operator according to its mathematical specification.