Anyscale Courses

Enabling End-to-End LLMOps on Michelangelo with Ray

Explore Uber's extension of Michelangelo for end-to-end LLMOps, leveraging Ray for scalable development with hundreds of A100 GPUs and integrating open-source techniques for efficient custom LLM creation.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Elevating DoorDash Model Training with Ray: From Good to Great

Explore DoorDash's journey in adopting Ray to enhance ML model training, addressing scalability, cost, and observability challenges while improving forecasting and training pipelines.

• YouTube
• 31 minutes
• On-Demand
• Free Video

OneDigital ML Platform: Unleashing the Power of Machine Learning at Scale

Explore OneDigital's journey in building a scalable ML platform using Ray and Anyscale. Learn about architecture, strategies, and retail use cases for advanced ML models.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Hyperparameter Tuning with Ray Tune for Next-Gen Training Platform at LinkedIn

Explore LinkedIn's cloud-native deep learning platform and its use of Ray(Tune) for hyperparameter tuning in AI model training, aiming to democratize AI for engineers.

• YouTube
• 26 minutes
• On-Demand
• Free Video

The Ray Dataplane: History and the Cloudsort World Record

Explore the evolution of Ray's dataplane, from zero-copy object store to powering Ray Data, and learn how it broke the Cloudsort world record for cost-effective 100TB data sorting.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Evaluating Large Language Models with Ray in Hybrid Cloud

Explore large language model evaluation using Ray in hybrid cloud environments. Learn auto-scaling, resource management, and unified workflows for efficient multi-task assessment across diverse domains.

• YouTube
• 29 minutes
• On-Demand
• Free Video

SkyML: Infra-less Machine Learning on Any Cloud

Explore SkyML for simplified, high-performance machine learning across clouds. Leverage best-of-breed accelerators, spot instances, and automatic resource management for cost-effective ML applications.

• YouTube
• 32 minutes
• On-Demand
• Free Video

Operationalizing Ray Serve on Kubernetes

Discover a new declarative REST API for Ray Serve, enabling seamless configuration and updates of applications within your MLOps lifecycle on Kubernetes.

• YouTube
• 30 minutes
• On-Demand
• Free Video

Scaling Training and Batch Inference - A Deep Dive into Ray AIR's Data Processing Engine

Dive into Ray AIR's data processing engine for efficient ML pipeline scaling. Learn distributed data sharding, parallel I/O, GPU optimization, and autoscaling for improved performance and scalability.

• YouTube
• 44 minutes
• On-Demand
• Free Video

Large-Scale Deep Learning to Augment Production RL Workloads at Riot Games

Learn to leverage large-scale deep learning for building game bots, predicting outcomes, and optimizing training processes in game development. Explore supervised learning techniques and scaling with Ray tools.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Cruise.data - A New Dataset Processing Pipeline for Cruise ML

Explore Cruise.data, a novel ML data pre-processing framework combining tf.data, PyTorch, and large-scale processing capabilities for efficient and scalable dataset handling in autonomous vehicle development.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Production RL and Decision-Making with RLlib

Learn to implement production-ready reinforcement learning and decision-making systems using RLlib, exploring real-world applications, challenges, and best practices.

• YouTube
• 29 minutes
• On-Demand
• Free Video

Large-Scale Distributed Training with TorchX and Ray

Learn to launch elastic large-scale distributed training jobs using TorchX and Ray, overcoming traditional barriers and simplifying the transition from research to production.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Large-Scale Data Shuffle in Ray with Exoshuffle

Explore high-performance large-scale data shuffling with Exoshuffle in Ray, outperforming Spark and achieving near-theoretical performance for ML applications.

• YouTube
• 26 minutes
• On-Demand
• Free Video

How Spotify Sped Up ML Research and Prototyping with Ray

Accelerate ML research and prototyping using Ray's distributed computing platform. Explore Spotify's journey, infrastructure integration, and best practices for enhanced model development and experimentation.

• YouTube
• 32 minutes
• On-Demand
• Free Video