Community Picks

The 2024 State of Data Engineering report discusses the influence of GenAI on software infrastructure, the expansion of product offerings due to the economic downturn, and the impact of open table formats and their catalogs in the data lake industry. It also highlights the importance of data version control and observability in AI/ML systems.

The State of Data Engineering 2024

KDnuggets

Explore 5 end-to-end open-source MLOps tools for training, tracking, deploying, and monitoring models in production. These tools provide enhanced data privacy and control over models and code.

5 Best End-to-End Open Source MLOps Tools

Towards AI

Learn how to build a comprehensive end-to-end CI/CD pipeline using GitHub Actions, Docker, and Cloud. The post covers pulling the production model from AWS RDS in MLflow and deploying the container locally and to the cloud.

Build end to end CICD pipeline using GitHub Actions-MLOps

Medium

The LLM Twin course teaches you how to design, train, and deploy a production-ready LLM twin using LLMs, vector DBs, and MLOps best practices. It covers the fine-tuning of LLMs on custom datasets at scale using Qwak and CometML.

How to fine-tune an Mistral7b LLM on custom dataset, with QLoRA, PEFT following MLOps practices

The practice of integrating machine learning models into the software development lifecycle for automated deployment, monitoring, and management. Readers can explore MLOps tools, processes, and best practices for building, deploying, and maintaining machine learning applications at scale.

Best of MLOps — May 2024