Hyperparameter Tuning with Ray Tune for Next-Gen Training Platform at LinkedIn
Offered By: Anyscale via YouTube
Course Description
Overview
Explore LinkedIn's cloud-native deep learning training platform on Kubernetes and learn how the training platform team leverages Ray(Tune) for hyperparameter tuning in their training pipeline. Discover how LinkedIn is addressing the surge in machine learning usage, driven by advanced models like LLMs, LPMs, and GNNs, by designing a flexible, user-friendly, and scalable training experience for AI engineers. Gain insights into how hyperparameter tuning is treated as a first-class citizen in the training platform, with the ultimate goal of democratizing AI for all engineers through AutoML. Understand the importance of this approach in enabling LinkedIn members to identify new opportunities, receive personalized recommendations, and connect with other professionals more effectively and efficiently.
Syllabus
Hyperparameter Tuning with Ray[Tune] for Next-Gen Training Platform at LinkedIn
Taught by
Anyscale
Related Courses
Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and OptimizationDeepLearning.AI via Coursera Machine Learning in the Enterprise
Google Cloud via Coursera Art and Science of Machine Learning 日本語版
Google Cloud via Coursera Art and Science of Machine Learning auf Deutsch
Google Cloud via Coursera Art and Science of Machine Learning en Español
Google Cloud via Coursera