"Machine Learning Pipeline" as a mental map should be "considered harmful"

Dec 31, 2023 ·

The article discusses the need for MLOps (machine learning operations) to move from manual operations towards managed machine learning systems using FTI Pipelines. MLOps is a set of processes and tools that enable organizations to manage the entire lifecycle of their machine learning models. This includes data collection, model training, deployment, monitoring, and optimization. With traditional manual MLOps processes, organizations are limited in terms of scalability, cost efficiency, and ability to effectively debug code errors.

FTI Pipelines is a platform that provides organizations with an automated system for managing the entire MLOps process. It automates data collection, model training, and deployment, making it easier for organizations to maintain the quality of their models and optimize them for production use. FTI Pipelines also enables organizations to debug code errors quickly, improving the performance of their models. Additionally, it allows organizations to deploy their machine learning models faster and at a lower cost than manual MLOps processes.

Overall, the article highlights the advantages of using FTI Pipelines as a managed MLOps system over manual MLOps processes. It demonstrates how FTI Pipelines can help organizations reduce costs, improve model quality, reduce time-to-deployment, and make debugging code errors simpler. The article also explains how FTI Pipelines can be used in various industries, such as healthcare and finance, to optimize machine learning models for better accuracy and performance.