The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Pickl AI

APRIL 27, 2023

Hence, introducing the concept of responsible AI has become significant. Responsible AI focuses on harnessing the power of Artificial Intelligence while complying with designing, developing, and deploying AI with good intentions. By adopting responsible AI, companies can positively impact the customer.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Python 52

The MLOps Blog

MARCH 21, 2023

” — Isaac Vidas , Shopify’s ML Platform Lead, at Ray Summit 2022 Monitoring Monitoring is an essential DevOps practice, and MLOps should be no different. Collaboration The principles you have learned in this guide are mostly born out of DevOps principles. My Story DevOps Engineers Who they are? Model serving.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69

Unite.AI

NOVEMBER 21, 2024

Archana Joshi brings over 24 years of experience in the IT services industry, with expertise in AI (including generative AI), Agile and DevOps methodologies, and green software initiatives. The evolution of AI is promising but also brings many corporate challenges, especially around ethical considerations in how we implement it.

DevOps 144

DevOps Automation Responsible AI Software Development 144