What we’re about
AI solutions need fresh, high-quality data for training, evaluation, and retraining — and they need it constantly and repeatedly. There is plenty of uncharted territory in the realms of data acquisition, data labeling, data augmentation, data quality evaluation, data debt, and data governance. We need people from all walks of ML along on the adventure as we explore efficient data engineering for real-life ML systems.
We welcome data scientists, researchers, ML engineers, and anyone who shares our belief that data and models are equally important in developing ML. Our vision is to pool our expertise and work together to build a framework for excellence across all stages of the Machine Learning life cycle. If you have practical experience to share or challenges to mull over, don’t hesitate to join the conversation! Our monthly meetups cover a wide range of topics with practical applications in areas like natural language processing, computer vision, search relevance, and much more.
