Learn Your Codebase: Fine-tuning CodeLlama with Flyte to Learn Flyte
Discover how to fine-tune LLMs on specific codebases using Flyte, an open-source orchestration platform. Explore multi-node, multi-gpu distributed training for efficient model adaptation with limited resources.
UnionML: A Microframework for Building Machine Learning Applications
Explore UnionML, a microframework simplifying ML application development. Learn to streamline the process from research to production, addressing common challenges in the ML lifecycle.
Training and Ensuring Reliability of ML Models - The Power of ArgoCD, Flyte, and Argo Workflows
Explore Wolt's approach to reliable ML model training and deployment using ArgoCD, Flyte, and Argo Workflows. Learn strategies for scalability, consistency, and collaboration in ML operations.
Efficient Data Parallel Distributed Training with Flyte, Spark and Horovod
Learn to optimize distributed training using Flyte, Spark, and Horovod for efficient data parallelism in machine learning workflows.
Self-serve Feature Engineering Platform Using Flyte and Feast
Explore a self-serve feature engineering platform leveraging Flyte and Feast technologies, enhancing data science workflows and machine learning model development.
Flyte - Cloud Native Machine Learning and Data Processing Platform
Explore Flyte, a cloud-native platform for machine learning and data processing, presented by Lyft engineers. Learn its features, benefits, and applications in modern data workflows.
The Data Pipelines Behind Forest Carbon Credits - Why Pachama Uses Flyte to Orchestrate Workflows
Explore how Pachama uses Flyte to manage complex data and ML pipelines for transparent forest carbon credit computation, including workload management, configuration, and lessons learned.
Scaling Open Source ML: How Wolt Uses Kubernetes to Deliver Great Food to Millions
Discover how Wolt leverages Kubernetes and open-source frameworks to scale machine learning operations, addressing challenges in forecasting, recommendations, and delivery time predictions for millions of users.
MLOps with Flyte - Challenges and Solutions in Machine Learning Operations
Explore MLOps challenges and solutions using Flyte, an open-source orchestration tool. Learn best practices for efficient ML model development and deployment at scale.
Prometheus in the MLOps Lifecycle
Explore Prometheus for monitoring ML deployments, addressing data drift, concept drift, and model metrics. Learn to enhance existing setups and integrate with Flyte, Seldon Core, or FastAPI.
Building Robust ML Production Systems Using OSS Tools for Continuous Delivery for ML
Learn to build robust ML production systems using open-source tools for continuous delivery, including workflow orchestration, data versioning, and model deployment and monitoring.
Enforcing Data Quality in Data Processing and ML Pipelines with Flyte and Pandera
Learn to enforce data quality in processing and ML pipelines using Flyte and Pandera, enhancing reliability and efficiency in data-driven projects.
Embracing Multi-Tenancy While Scaling MLOps
Explore multi-tenancy in MLOps: efficient resource sharing, isolation, and security for scaling ML operations. Learn implementation strategies using open-source tools like Flyte for cost-effective and secure multi-tenant environments.
Flyte - Production-Grade Data and Machine Learning Orchestration
Explore Flyte, an open-source platform for scalable, repeatable, and maintainable data and machine learning orchestration, addressing key challenges in MLOps and data processing.
Optimizing Kubernetes Cluster Scaling for Advanced Generative Models
Explore advanced techniques for scaling Kubernetes clusters to support complex generative models, leveraging tools like Flyte, MLflow, and Kubeflow for efficient deployment and management.
Embracing Multi-Tenancy While Scaling MLOps
Learn strategies for implementing multi-tenancy in MLOps, covering resource sharing, isolation, security, and efficient scaling using open-source tools like Flyte for improved ML operations.
Observability in the MLOps Lifecycle with Prometheus
Explore MLOps monitoring with Prometheus, covering ML deployment challenges, data drift, and model metrics. Learn to enhance existing systems and integrate with tools like Flyte, Seldon Core, and FastAPI.
How Spotify Leverages Flyte to Coordinate Financial Analytics Company-Wide
Explore Spotify's use of Flyte for financial analytics, covering MLOps/DataOps needs, best practices for ML/data apps, and how Flyte bridges technical gaps for users of varying proficiency.
Secure AI Orchestration: Mitigating Model-centric Attacks with Flyte
Discover how to protect AI systems from model-centric attacks, focusing on code injection and LLM vulnerabilities, while implementing security measures using Flyte orchestration and open-source tools.
Systems Engineering in Machine Learning - Navigating Low-Level Challenges
Explore systems engineering in ML with Andrew Dye, discussing low-level work, blending disciplines, and ML infrastructure challenges. Gain insights on distributed training, managing scale, and bridging gaps between firmware and MLOps.
MLOps vs ML Orchestration - Exploring Challenges and Community-Driven Development
Explore MLOps vs ML Orchestration with Ketan Umare, discussing Union.AI, Flyte, community-driven development, real-time data handling, and democratizing machine learning for broader accessibility and efficiency.