Unite.AI

OCTOBER 20, 2023

Promote AI transparency and explainability: AI transparency means it is easy to understand how AI models work and make decisions. Explainability means these decisions can be easily communicated to others in non-technical terms.

Responsible AI 283

Responsible AI Generative AI AI AI 283

Viso.ai

APRIL 25, 2024

Deep learning models are black-box methods by nature, and even though those models succeeded the most in CV tasks, explainability is still poorly assessed. Explainable AI improves the transparency of those models making them more trustworthy. Do the data agree with harmful stereotypes?

Computer Vision 52

Computer Vision Categorization Algorithm Explainability 52

DataRobot Blog

DECEMBER 20, 2022

As discussed in the previous article , these challenges may include: Automating the data preprocessing workflow of complex and fragmented data. Monitoring models in production and continuously learning in an automated way, so being prepared for real estate market shifts or unexpected events.

Explainability 59

Explainability Automation Machine Learning AI 59

Pickl AI

MAY 15, 2024

Understanding the Challenges of Scaling Data Science Projects Successfully transitioning from Data Analyst to Data Science architect requires a deep understanding of the complexities that emerge when scaling projects. But as data volume and complexity increase, traditional infrastructure struggles to keep up.

Data Scientist 52

Data Scientist Data Science Machine Learning Data Quality 52