ODSC - Open Data Science

MAY 10, 2023

Data-centric AI, in his opinion, is based on the following principles: It’s time to focus on the data — after all the progress achieved in algorithms means it’s now time to spend more time on the data Inconsistent data labels are common since reasonable, well-trained people can see things differently.

Data Scientist 87

Data Scientist Data Science Deep Learning Deep Learning 87

Pickl AI

SEPTEMBER 5, 2024

Data Preparation: Cleaning, transforming, and preparing data for analysis and modelling. Collaborating with Teams: Working with data engineers, analysts, and stakeholders to ensure data solutions meet business needs.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Precisely

SEPTEMBER 26, 2024

Above all, you must remember that trusted AI starts with trusted data. And trusted data requires data integrity: data that’s accurate, consistent, and contextualized. Without proper data preparation, you risk issues like bias and hallucination, inaccurate predictions, poor model performance, and more. “If

AI 76

AI AI Data Governance Data Quality 76

Iguazio

MARCH 20, 2025

To see the complete conversation and dive into their insights, watch the webinar here. Companies are building AI tools and frameworks that empower engineers to integrate AI into applications without needing deep expertise in ML. See the webinar for more Gartner trends. Watch the webinar to see. Whats Next in 2025?

AI 59

AI AI Data Pipeline Data Scientist 59