LEIP Design¶
LEIP Design is an innovative Python library designed to streamline and orchestrate the composition, modification, and execution of machine learning workflows, from data ingestion and model development to optimization and deployment.
Creating machine learning pipelines often requires expertise in multiple languages, frameworks, and hardware configurations. Because each change to a model must be tested and evaluated for accuracy and performance, calibrations are time-consuming and resource-intensive operations. And even then, customized workflows reduce repeatability and increase development time.
LEIP Design simplifies this process with the introduction of recipes. Each step in the recipe, called a node, is built with ingredients you select from a pantry and connect with other nodes to build your machine learning pipeline. You can then use Design to check and validate the feasibility of your recipe, explore alternatives, and execute the pipeline.
If you want to accelerate the process of prototyping, fine-tuning, and deploying your machine learning models, you should use LEIP Design.
In this Documentation¶
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Start here for step-by-step instructions for installing and getting started with LEIP Design
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Guides that cover key operations and common tasks
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Reference documentation for the LEIP Design API
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Learn more about LEIP Design