LinkedIn Dataset

LinkedIn datasets are used extensively to develop and improve various machine learning models for applications such as content recommendation, job matching, and advertising. Current research focuses on large-scale model architectures like Graph Neural Networks (GNNs), transformer-based LLMs, and deep ranking models (e.g., Residual DCNs), often incorporating techniques like meta-learning and multi-task contrastive learning to enhance personalization and efficiency. These efforts aim to optimize key metrics like user engagement, job application rates, and advertising click-through rates, contributing valuable insights into the development and deployment of large-scale AI systems in a real-world setting. The resulting advancements in model architectures, training strategies, and deployment techniques have broad implications for the broader machine learning community and practical applications in other large-scale online platforms.