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KDD 2024Workshop Summaries

The Third Workshop on Applied Machine Learning Management

Dmitri Goldenberg, Shir Meir Lador, Elena Sokolova, Lin Lee Cheong, Mohak Sukhwani, Saloni Potdar

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.1145/3637528.3671478 ↗

摘要

Machine learning applications are rapidly adopted by industry leaders in any field. The growth of investment in AI-driven solutions,including the emerging field of General AI (GenAI), has created new challenges in managing Data Science and ML resources, people and projects as a whole. The discipline of managing applied machine learning teams, requires a healthy mix between agile product development tool-set and a long term research oriented mindset. The abilities of investing in deep research while at the same time connecting the outcomes to significant business results create a large knowledge based on management methods and best practices in the field. The Third KDD Workshop on Applied Machine Learning Management brings together applied research managers from various fields to share methodologies and case-studies on management of ML teams, products, and projects, achieving business impact with advanced AI-methods.