Data-Centric AI
This Data-Centric AI focuses on improving AI systems by enhancing the quality and management of the data used in training rather than solely tweaking algorithms. It emphasizes creating high-quality, well-labeled datasets and addressing data issues such as bias, imbalance, or noise. This approach aims to achieve better AI performance and robustness by refining the data itself.
Related Conference of Data-Centric AI
August 10-11, 2026
12th World Congress on Computer Science, Machine Learning and Big Data
London, UK
October 22-23, 2026
6th International Conference on Renewable Energy and Resources
Vancouver, Canada
December 07-08, 2026
12th International Conference and Exhibition on Mechanical & Aerospace Engineering
Dubai, UAE
December 09-10, 2026
25th International Conference on Big Data & Data Analytics
Amsterdam, Netherlands
Data-Centric AI Conference Speakers
Recommended Sessions
- Federated Learning
- AI Ethics and Responsible AI
- AI in Cybersecurity
- AI in Finance
- AI in Healthcare
- AI-Powered Personalization
- Artificial Neural Network
- AutoML and Low-Code Machine Learning
- Causal Inference
- Data Democratization
- Data Privacy and Security
- Data Science
- Data-Centric AI
- Deep Learning
- Edge AI and IoT Analytics
- Generative AI
- Graph Neural Networks
- Large-Scale Data Engineering
- Multi-Modal Learning
- Quantum Machine Learning
- Real-Time Data Streaming
- Reinforcement Learning
- Synthetic Data
Related Journals
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