The Ops in MLOps - Cost Predictive, Security Compliant, and Data Governance Techniques
Explore techniques for creating ML environments with cost predictability, security compliance, and proper data governance. Focus on the often-overlooked Ops components of MLOps.
Unlock the Power of MLFlow with Multi-Cloud Compute Infrastructure
Harness MLFlow's potential using multi-cloud compute infrastructure. Learn integration techniques, architectural considerations, and scaling strategies for effective ML training and deployment across clouds.
Challenges for ML Operations in a Fast Growing Company
Explore ML operations challenges in rapidly growing companies. Learn strategies for scalable platforms, efficient model training, and balancing distributed vs. non-distributed applications. Gain insights on developer ergonomics and best practices.
Continuations: The Magic Behind Virtual Threads in Java
Explore the power of Continuations in Java, the mechanism behind virtual threads. Learn how to implement a simple VirtualThread class using the Continuation API for enhanced scalability.
Lessons Learned: The Journey to Real-Time Machine Learning at Instacart
Explore Instacart's transition to real-time machine learning, focusing on infrastructure, use cases, challenges, and key lessons for implementing ML in a dynamic marketplace.
Supercharging Recommender Systems - Unleashing the Power of Distributed Model Training
Explore distributed model training techniques to enhance recommender systems, boosting performance and scalability for production environments.
Wanted: A Silver Bullet MLOps Solution for Enterprise
Explore key learnings from a 4-year MLOps journey in pharmaceutical research, addressing challenges in tool selection, user diversity, and scalable solutions for operationalizing ML models.
From Idea to Production: AI Infrastructure for Scaling LLM Applications
Explore strategies for scaling LLM applications from beta to production, addressing challenges and building adaptable AI infrastructure for evolving models and workflows.
Enhancing Cloud-native Security - Speed, Accuracy, and Context for Effective Threat Response
Develop a holistic strategy for cloud security with advanced monitoring, threat intelligence, and adaptive incident response to address evolving challenges.
Minutes, Not Months - Lightning Fast Cloud PKI Solutions
Explore modern PKI for proven security and identity at scale, covering IoT, in-country, on-prem, and hybrid landscapes. Learn cloud transformation fundamentals.
Deploying Generative AI Models - Best Practices and Interactive Example
Explore best practices for deploying generative AI models at scale, with an interactive example using UbiOps for serverless and cloud-agnostic implementation.
Critical Decisions - Live Services, Generative AI, and Game Infrastructure Architecture
Explore integrating generative AI in games, architect for scalability, and future-proof development with insights from Google Cloud's product manager.
Scaling Live Service Games on the Cloud with Google Kubernetes Engine
Build dedicated game server environments with Google Kubernetes Engine for fully managed, resilient, cost-effective, and flexible next-generation servers.
The Ops in MLOps: Creating Cost-Effective and Compliant ML Environments
Explore techniques for creating cost-effective, secure, and compliant ML environments with proper data governance in MLOps.
Deploy High Scale ML Models Without the Hustle
Learn to build and operate production-grade ML systems, from model training to deployment and monitoring, using the Qwak platform for efficient, high-scale solutions.
Machine Learning for Entertainment - Challenges and Opportunities
Explore challenges and solutions in ML for streaming services, including personalization, content understanding, and ads targeting. Learn about balancing metrics, feedback loops, and algorithmic fairness.
Scaling ML Embedding Models to Serve a Billion Queries
Learn to scale ML embedding models for visual search, exploring eBay's architecture, workflows, and solutions to handle billions of queries efficiently.
Supercharging MLOps with the Petuum Platform
Explore innovations in Composable, Automatic, and Scalable ML (CASL) and their role in transforming MLOps into a repeatable assembly-line process using the Petuum Platform.
Human Centric MLOps - Why Productivity Matters the Most
Explore human-centric MLOps and its impact on productivity. Learn how focusing on people, not just systems, can revolutionize machine learning operations and drive innovation.
Deploying and Managing Machine Learning Models at Scale - A Hands-On Workshop
Deploy and manage ML models at scale. Hands-on workshop covers creation, deployment, monitoring, and management using real-life scenarios. Gain practical experience with Seldon Deploy, explainers, and outlier detection.
Critical Use of MLOps in Finance Using Cloud-Managed ML Services That Scale
Leverage MLOps to improve quality and consistency of machine learning solutions in finance. Accelerate model experimentation, deployment, and tracking using cloud-managed services for efficient scaling.