Anyscale Courses

Supercharging ETL and Analytics with Ray and Daft

Discover how Daft library enhances Ray clusters with distributed ETL capabilities, enabling seamless data processing, analytics, and ML/AI integration for scalable, high-performance workflows.

• YouTube
• 11 minutes
• Self-Paced
• Free Video

Distributed Mesh Processing and Geometric Deep Learning for Wind Prediction

Discover how Ray's distributed computing powers real-time wind prediction in urban design through mesh processing, geometric deep learning, and CFD data analysis for architectural innovation.

• YouTube
• 14 minutes
• Self-Paced
• Free Video

From Spark to Ray - Data Processing Revolution with Daft

Discover how CSS revolutionizes machine learning infrastructure using Daft and Ray, showcasing real-world applications that streamline data processing and ETL workflows for enhanced efficiency and scalability.

• YouTube
• 14 minutes
• Self-Paced
• Free Video

How Datadog is Transforming Time Series Forecasting with Toto

Discover how Toto, a Time Series-Optimized Transformer, revolutionizes forecasting through advanced architecture and trillion-point training data, enabling precise zero-shot predictions for observability metrics.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Leveraging LLMs and LangGraph for Flight Data Retrieval

Discover how FlightAware combines LLMs and LangGraph to create an intelligent chatbot interface for flight searches, featuring practical implementation examples and workflow orchestration techniques.

• YouTube
• 14 minutes
• Self-Paced
• Free Video

Building Scalable Cross-Modal Search with Ray

Discover how to build a powerful fashion image retrieval system using Ray and Pinecone, enabling efficient text-to-image and image-to-image search with CLIP embeddings and vector similarity.

• YouTube
• 11 minutes
• Self-Paced
• Free Video

Model Training on Snowflake with Ray

Discover how to leverage Snowflake Container Runtime and Ray for efficient, scalable model training through a practical demonstration of performance optimization techniques.

• YouTube
• 14 minutes
• Self-Paced
• Free Video

Scaling LLM Inference - AWS Inferentia Meets Ray Serve on EKS

Discover how to build scalable, cost-effective LLM inference infrastructure using Ray Serve and AWS Inferentia on Amazon EKS, optimizing deployment of models like Llama2 and Mistral-7B.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Ray on Kubernetes - Powering Quantitative Research at Scale

Discover how Ray on Kubernetes revolutionizes quantitative research with scalable infrastructure supporting 100,000 CPU cores, spot instances, and seamless GPU integration for high-performance trading operations.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Akash Network - Powering Ray on an Open Source Super Cloud

Discover how Akash Network's open-source super cloud platform revolutionizes distributed computing and AI workloads, featuring real-world applications and live demonstrations of Ray clusters with vLLM and Llama-3.1.

• YouTube
• 16 minutes
• Self-Paced
• Free Video

Accelerating Princeton's Computational Science with Ray

Discover how Princeton University revolutionizes academic research computing by implementing Ray across campus clusters, multi-institutional systems, and hybrid cloud environments for enhanced ML and HPC capabilities.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Anyscale's Ray Data: Revolutionizing Batch Inference

Explore Anyscale's innovative approach to optimizing large-scale batch inference using Ray Data and infrastructure advancements, offering insights to enhance ML deployments and reduce operational costs.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

Airbnb's LLM Evolution: Fine-Tuning with Ray

Explore Airbnb's journey in evolving LLM fine-tuning support using Ray, showcasing efficient techniques and real-world applications in customer support through SFT and DPO.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Pinterest's ML Evolution: Distributed Training with Ray

Uncover Pinterest's ML journey in optimizing recommender systems using Ray for distributed training. Explore challenges, solutions, and innovations in scaling data-intensive workloads across thousands of jobs.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Meta's Roadmap for Full Stack AI - Insights from Llama Ecosystem

Explore Meta's roadmap for full-stack AI with Joe Spisak. Gain insights into the Llama ecosystem, building generative AI agents at scale, and leveraging open AI for innovation and application development.

• YouTube
• 38 minutes
• Self-Paced
• Free Video