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.
Building an ML Platform from Scratch
Develop a customizable ML platform using open-source tools. Learn to integrate Cookiecutter, DVC, MLFlow, KFServing, and more for a flexible solution tailored to your organization's needs.
Automatic ML Model Containerization: Best Practices and Tools
Explore best practices for containerizing ML models for production inference. Learn about secure, multi-tenant image builds, avoiding lock-in, and tools like chassis.ml and Open Model Interface for seamless integration.
Using Reproducible Experiments to Create Better Machine Learning Models
Enhance ML model efficiency through reproducible experiments. Learn to track hyperparameter, code, and data changes using DVC for grid and random search tuning methods.
Taking MLOps 0-60: How to Version Control, Unify Data and Manage Code Lifecycles
Explore MLOps fundamentals, focusing on version control, data unification, and code lifecycle management for reliable and adaptable machine learning systems.
SLA-Aware Machine Learning Inference Serving on Serverless Computing Platforms
Explore adaptive batching for efficient ML inference serving on serverless platforms. Learn to optimize costs and ensure SLA compliance using MLProxy for improved performance.
Shopify's Machine Learning Platform Journey: Building Merlin with Open Source Tools
Explore Shopify's journey in building Merlin, an open-source ML platform. Gain insights into the architecture, technologies, and tools used to scale machine learning work effectively.
Feature Engineering Made Simple
Master feature engineering techniques to streamline your machine learning workflow. Explore systematic approaches using Anovos, an open-source library for efficient data processing and model building.
MLOps is Just HPC in Disguise - A Real-World, No-Nonsense Guide to Upgrading Your Workflow
Upgrade your ML workflow with efficient tools and techniques for automating tasks, managing resources, and streamlining production deployment in this practical guide to MLOps.
Reproducible Machine Learning - How Not to Repeat the Past
Explore techniques for organizing and reproducing deep learning experiments, including standardized logging, versioning, and templated workflows. Enhance collaboration and minimize duplication in ML projects.
MLOps for Fairness - Creating Comprehensive Fairness Workflows
Explore MLOps techniques for identifying, measuring, and mitigating bias in ML systems at scale. Learn to create comprehensive fairness workflows using Python tools for industry-level challenges.
Accelerating Deployment of AI with MLOps Orchestration
Explore MLOps orchestration to simplify AI deployment using Kubernetes and open-source tools. Learn to build efficient ML pipelines, from data preparation to model monitoring, accelerating business value across various use cases.
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.
Testing Recommender Systems in the Wild - MLOps World
Explore behavioral testing for recommender systems using RecList. Scale up real-world testing in research and production with hands-on coding and practical examples.
Automated Machine Learning Tuning with FLAML
Explore automated machine learning and tuning using FLAML, a fast Python library. Learn to automate ML tasks, perform general tuning, and conduct zero-shot AutoML efficiently.
Top 5 Lessons Learned in Helping Organizations Adopt MLOps Practices
Discover key insights and strategies for implementing MLOps practices at scale. Learn common challenges and effective mitigation techniques for successful organizational adoption.
Implementing MLOps Practices on AWS using Amazon SageMaker
Implement ML pipelines with CI/CD practices using SageMaker Pipelines. Gain hands-on experience in MLOps, incorporating DevOps principles into machine learning workflows for scalable and efficient model deployment.
Lessons Learned from DAG-Based Workflow Orchestration
Explore DAG-based workflow orchestration challenges and learn about Prefect Orion's DAG-less system for enhanced runtime flexibility and developer experience in data pipelines.
Shopify's Machine Learning Platform Journey: Building Merlin with Open Source Tools
Explore Shopify's journey in building Merlin, an open-source ML platform. Gain insights into the architecture, technologies, and tools used to scale machine learning work effectively.
WarpDrive: Orders of Magnitude Faster Multi-Agent Deep Reinforcement Learning on a GPU
Accelerate multi-agent deep reinforcement learning with WarpDrive, an open-source framework enabling end-to-end GPU execution. Explore features like automatic GPU tuning and distributed training for improved efficiency and scalability.
Hands-on: A Beginner-Friendly Crash Course to Kubernetes
Découvrez les bases de Kubernetes et des applications Cloud Native. Explorez l'orchestration de conteneurs et le déploiement d'applications dans un environnement cloud moderne.