Data Science

The Importance of Privacy Measurement in Machine Learning Models

Testing the Vulnerability of Regression Models to Data Manipulation

Accuracy Degradation Factor: Quantifying Model Performance Shifts Before They Occur

Introducing Holistic AI OSL - An Open-Source Library for Responsible AI Systems

What You Need to Know about Knowledge Graphs and RAG Systems

LLM Summarization Metrics

Technical Approaches to Managing Personal Data in Large Language Models

Enhancing Transparency in AI: Explainability Metrics via SHAP Feature Importance with Holistic AI Open-Source Library

Enhancing Transparency in AI: Explainability Metrics for Machine Learning Predictions

Enhancing Transparency in AI: Explainability Metrics via LIME with Holistic AI Library

Holistic AI Library and MLFlow: Creating an End-to-End Application

Six Methods to Mitigate Bias in Multiclassification Machine Learning Models

Visualising Bias Metrics: Insights from Holistic AI's Open-Source Library

Explaining Machine Learning Outputs: The Role of Feature Importance

Debiasing Artificial Neural Networks with Holistic AI and PyTorch

How to Create Interactive Visualisations in Colab with Holistic AI and Plotly

Build Your Own Bias Measuring and Mitigation Dashboard in 5 Steps

Using Python to Mitigate Bias and Discrimination in Machine Learning Models

Bias Mitigation Strategies and Techniques for Classification Tasks

How to Make Artificial Intelligence Safer

We are in the Age of AI Economies

Measuring and Mitigating Bias: Introducing Holistic AI's Open-Source Library

SHAP Values: An Intersection Between Game Theory and Artificial Intelligence

Practical and Societal Dimensions of Explainable AI

The Rise of Large Language Models: Galactica, ChatGPT, and Bard

Insightful Resources for Uncovering Bias in English Speech Recognition

Disparate Impact in Bias Audits: Evaluating the DCWP’s Impact Ratio Metrics for Regression Systems