Data|Centric AI
Introduction to Data-Centric AI
The first-ever course on data-centric AI. Learn how you can train better ML models by improving the data.
Data-centric AI is the discipline of systematically engineering the data used to build an AI system. Explore Topics.
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Data Centric Machine Learning - Landing AI
A Data-Centric AI approach involves building AI systems with quality data — with a focus on ensuring that the data clearly conveys what the AI must learn.
[2303.10158] Data-centric Artificial Intelligence: A Survey - arXiv
Abstract page for arXiv paper 2303.10158: Data-centric Artificial Intelligence: A Survey.
What is Data-Centric AI? - van der Schaar Lab
Data-centric AI views model or algorithmic refinement as less important, and instead seeks to systematically improve the data used by ML systems.
Andrew Ng: Unbiggen AI - IEEE Spectrum
The AI pioneer says it's time for smart-sized, “data-centric” solutions to big issues.
Why it's time for 'data-centric artificial intelligence' - MIT Sloan
Why It Matters. Machine learning pioneer Andrew Ng argues that focusing on the quality of data fueling AI systems will help unlock its full ...
Data-centric AI: A complete primer - Snorkel AI
Data-centric AI is all about iterating and collaborating on the data used use to build AI systems and doing so programmatically.
Definition of Data-Centric AI - IT Glossary - Gartner
Data-centric AI is an approach that focuses on enhancing and enriching training data to drive better AI outcomes, as opposed to a model-centric approach ...
A curated, but incomplete, list of data-centric AI resources. - GitHub
What is the Data-centric AI Framework? framework. Data-centric AI framework consists of three goals: training data development, inference data development, and ...
Data-centric AI | The ODI - Open Data Institute
We use it to refer to the entire socio-technical data infrastructure of AI – this includes data assets, tools, standards, practices, and communities.
Data-Centric Approach vs Model-Centric Approach in Machine ...
As a result, the AI community believes that model-centric machine learning is more promising. While focusing on the code, data is frequently ...
YData data quality for Data Science | Synthetic data Data-Centric AI
YData is easy to use and highly trustworthy.“ ... “It is a must-use tool for any data science project. It really helps to understand several key features of your ...
Data-Centric AI in the Age of Large Language Models - arXiv
This position paper proposes a data-centric viewpoint of AI research, focusing on large language models (LLMs).
Data-Centric Artificial Intelligence | Business & Information Systems ...
Data-centric AI represents an emerging paradigm that emphasizes the importance of enhancing data systematically and at scale to build effective and efficient ...
DMLR Data-centric Machine Learning Research
This is the fifth edition of highly successful workshops focused on data-centric AI, following the success of the Data-Centric AI workshop at NeurIPS 2021, ICML ...
GitHub - HazyResearch/data-centric-ai
We're collecting (an admittedly opinionated) list of resources and progress made in data-centric AI, with exciting directions past, present and future.
Sensor Tower acquires market intelligence platform data.ai
data.ai joins Sensor. The addition of data.ai's product, input data, and team significantly advances Sensor Tower as a leader in the digital economy ...
Data Centric AI - NeurIPS 2024
Workshop. Data Centric AI. Andrew Ng · Lora Aroyo · Greg Diamos · Cody Coleman · Vijay Janapa Reddi · Joaquin Vanschoren · Carole-Jean Wu · Sharon Zhou ...