List: Trustworthy AI | Curated by Wilfried Hoge

Jun 18, 2023
15 stories
Trustworthy AI
In
IBM Data Science in Practice
by
Carolyn Saplicki
AI Fairness in IndustryBy Erika Agostinelli (IBM Senior Data Scientist), Stefan van der Stockt (IBM Lead Data Scientist, Master Inventor) and Carolyn Saplicki…
May 26, 2023
May 26, 2023
In
TDS Archive
by
Marco Tulio Ribeiro
Testing Language Models (and Prompts) Like We Test SoftwareTL;DR: You should
May 24, 2023
3
May 24, 2023
3
Alexander Lang
Deploy Watson NLP models in IBM Cloud Pak for DataHigh-Quality Text Analysis in your OpenShift environment
Apr 10, 2023
Apr 10, 2023
In
IBM Data Science in Practice
by
Carolyn Saplicki
Deploying and Monitoring Deep Learning Models on Cloud Pak for DataBy Courtney Branson, Advisory Data Scientist, and Carolyn Saplicki, Senior Data Scientist
Mar 21, 2023
Mar 21, 2023
Alexander Lang
Turn Data into Feature Groups with IBM Cloud Pak for DataCreate, share and reuse curated feature data across your data science projects
Mar 3, 2023
Mar 3, 2023
Lukasz Cmielowski, PhD
Large tabular data & AutoAIwritten by: Lukasz Cmielowski, PhD, Thomas Parnell
Dec 1, 2022
1
Dec 1, 2022
1
Snehal Gawas
What’s new in Watson Studio on IBM Cloud Pak for Data 4.6IBM Watson Studio empowers customers to build, run and manage AI models, and optimize decisions on IBM Cloud Pak® for Data platform.
Nov 30, 2022
Nov 30, 2022
In
IBM Data Science in Practice
by
Ross Lewis
Explainability and Trust in Machine LearningThe importance of explainable AI and data science
Nov 1, 2022
Nov 1, 2022
In
IBM Data Science in Practice
by
Christian Bernecker
An enterprise design pattern for MLOps & DataOps on unified data and AI platformsThis article describes a reusable enterprise design pattern for MLOps / AIOps and DataOps tasks that helps to simplify and automate how…
Nov 1, 2022
Nov 1, 2022
In
IBM Data Science in Practice
by
Rakshith Dasenahalli Lingaraju
Concurrent load testing for ML models deployed in Cloud Pak using LocustBefore enterprises decide to productionalize a Machine Learning model and make it available for online consumption, the model undergoes…
Oct 3, 2022
Oct 3, 2022
In
IBM Data Science in Practice
by
Rakshith Dasenahalli Lingaraju
Machine learning model replacement in complex and agile micro services architecturesThis article provides an insider view on managing complex ML model deployments from the lens of operational excellence, challenges and…
Oct 3, 2022
Oct 3, 2022
In
IBM Data Science in Practice
by
Rakshith Dasenahalli Lingaraju
Rapid scaling and deployment of machine learning models in mission critical systemsOne of the main issues in MLOps(machine learning operations) is how to manage and maintain various KPIs of productionized ML model (API)…
Oct 3, 2022
Oct 3, 2022
Maria Gusarova
Explain Any Machine Learning Model in Python, SHAPA Comprehensive Guide to SHAP and Shapley Value; Explainable machine learning with a single function call
Sep 22, 2022
4
Sep 22, 2022
4
In
IBM Data Science in Practice
by
Maleeha k
Practitioner’s guide to Trustworthy AICo-authored by Maleeha Koul, Data Scientist with IBM Data Science Elite, and Courtney Branson, Data Scientist with Expert Labs Trustworthy…
Sep 19, 2022
Sep 19, 2022
In
IBM Data Science in Practice
by
Vera Qingzi Liao
Building Explainable AI Applications with Question-Driven User-Centered DesignA method you can follow to build XAI applications, developed through our research and collaboration with IBM Design for AI
Sep 9, 2021
Sep 9, 2021