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This module is designed to provide all participants with the necessary background, particularly for those who are new to the theory and fundamentals of modern ML.

The aim of ML x Cases track is to provide you with a training on real-world issues and processes related to ML development/implementation process. This will range from efficient and repeatable approaches to data collection, enrichment and cleaning, and labelling, to transfer learning use cases of pre-trained SOTA models and their fine-tuning to achieve good performance on a domain-specific task.

This track explored the intersection of machine learning, natural language processing, and financial systems.

This track focused on the use of machine learning in healthcare and biomedical research.


General Chair
AI for Global Goals

Program Chair
Elandi

Area Chair
Huawei

Area Chair
Mozilla AI

Area Chair
Uni of Oxford

Area Chair
Uni of Southern California

Area Chair
Moonsong Labs


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