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
April 23-24, 2025
18th International Conference on Tissue Engineering and Regenerative Medicine
Aix-en-Provence, France
May 14-15, 2025
4th International conference on Information Technology, Data Science and Digital Health
Paris, France
July 28-29, 2025
3rd World Summit on Big Data, Machine Learning and Artificial Intelligence
Vancouver, Canada
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
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