Hazelcast 5.2 - What's Next?
Explore the latest features and future developments of Hazelcast 5.2, gaining insights into its enhanced capabilities and potential applications.
Creating and Submitting Scala Jobs to Spark Clusters Using Airflow
Build end-to-end data engineering project using Airflow, Docker, Spark, Scala, Python, and Java. Create and submit jobs to Spark clusters, process data, and view real-time results.
End-to-End Data Engineering with Apache Airflow, Docker, and Spark Clusters - Using Python, Scala, and Java
Build an end-to-end data engineering project using Apache Airflow, Docker, Spark Clusters, Scala, Python, and Java. Create and submit jobs in multiple languages to a Spark cluster for processing and real-time results.
Creating and Submitting Java Spark Jobs to Spark Clusters
Create and submit Java Spark jobs to clusters. Learn end-to-end data engineering with Airflow, Docker, Spark, Scala, Python, and Java. Build and process jobs in multiple languages for live results.
Flower - An Opensource Federated Learning Framework
Explore Flower, an open-source federated learning framework, and its applications in collaborative machine learning across distributed datasets.
KSVD.jl: A Case Study in Performance Optimization
Explore performance optimization techniques for K-SVD algorithm implementation, including execution order adjustments, single-core optimizations, multi-threading, and distributed computing.
Parallel Algebraic Multigrid in Julia with PartitionedArrays.jl - JuliaCon 2024
Explore parallel algebraic multigrid methods in Julia using PartitionedArrays.jl. Learn about recent updates, implementation strategies, and advantages over traditional MPI-based approaches for large-scale linear solvers.
DistributedWorkflow.jl - A Task-Based Workflow System Interface
Explore DistributedWorkflow.jl, a Julia interface for task-based workflow management. Learn to build domain-specific workflows, leverage dynamic scheduling, and simplify parallel distributed application development for HPC and domain scientists.
Pandas Parallel Transformations with Dask and Pandarallel
Optimize data processing with Dask and Pandarallel for faster Pandas transformations. Learn parallel computing techniques to enhance performance.
Introduction to Numerical Computation Applications Using Ubuntu WSL
Explore numerical computing on Ubuntu WSL for efficient solver development and deployment, with practical examples and insights on streamlining workflows for complex engineering problems.
Running ML Workloads with AWS Purpose-Built ML Accelerators and Ray
Discover AWS Trainium and Inferentia ML accelerators for high-performance, cost-effective Generative AI in the cloud. Explore native support for these accelerators in Ray.
Wind Farm Optimization Using Reinforcement Learning and Large-Scale Simulation
Optimize wind farm energy production using deep reinforcement learning and large-scale simulations. Boost annual output by 1-2% through advanced yaw control strategies.
Accelerating Scientific Discovery with AI and Quantum Computing
Explore cutting-edge insights on distributed computing and AI from IBM's Dario Gil in this Ray Summit 2022 keynote address.
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.
Managed Cloud Infrastructure for LLMs
Explore solutions for LLM infrastructure challenges, including cost reduction, GPU availability, scalability, and cloud resource management. Learn to accelerate AI development and deployment.
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.
KubeRay: A Ray Cluster Management Solution on Kubernetes
Explore KubeRay's integration with Kubernetes, its capabilities for Ray cluster management, and performance benchmarks for simplified deployment of Ray applications.
Scaling AI Health Assistants: Challenges and Solutions
Explore challenges and solutions in scaling AI health assistants, focusing on model management, state persistence, and system reliability. Learn key principles for building scalable AI products using Ray.
Lessons From Fine-Tuning Llama-2
Explore insights from fine-tuning Llama-2 for specialized applications. Learn setup, infrastructure, and efficiency techniques to outperform GPT-4 in specific scenarios using Anyscale and Ray.
Developing and Serving RAG-Based LLM Applications in Production
Learn to develop, evaluate, and scale RAG-based LLM applications for production, including advanced topics like hybrid routing to bridge the gap between open-source and closed LLMs.
Orchestrating and Distributing Hybrid Quantum Computing Experiments
Explore orchestration and distribution techniques for hybrid quantum computing experiments with insights from Agnostiq's Head of R&D.