Machine Learning Designer uses pipelines to build and debug models. Start by planning and creating a pipeline, then organize the various components according to your processing and scheduling logic. Machine Learning Designer offers multiple methods for pipeline creation, including demos to show you how to create a pipeline by using a template and how to create a custom pipeline.
Use a preset template
Designer offers a variety of built-in templates tailored to different frameworks and the diverse needs of industry scenarios. You can use a preset template to create a pipeline, adjust the components or their configurations, and swiftly construct and deploy a model that aligns with your requirements. This demo shows how to create a pipeline using the heart disease prediction template, see Demo for creating a pipeline by using a template.
Custom pipeline
This demo walks you through the creation of a blank pipeline for developing a binary classification model for heart disease prediction. Starting from scratch, you will engage in data preprocessing, model prediction, and evaluation, culminating in a fully visualized model building and deployment process. For more information, see Custom pipelines.