{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Implement ML pipeline Using the AWS Step Functions Data Science SDK\n", "\n", "1. [Introduction](#Introduction)\n", "1. [Setup](#setup)\n", "1. [Create Resources](#Create-Resources)\n", "1. [Build a Machine Learning Workflow](#Build-a-Machine-Learning-Workflow)\n", "1. [Run the Workflow](#Run-the-Workflow)\n", "1. [Clean Up](#Clean-Up)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "## 1. Introduction\n", "\n", "This notebook describes how to use the AWS Step Functions Data Science SDK to create a machine learning pipeline across data preparation, model training, model evaluation and model register. The defintion of workflow as beflow:\n", "\n", "
Name | \n", "Status | \n", "Started | \n", "End Time | \n", "
---|---|---|---|
\n", " b1219731-3692-4d0d-b393-e37698b6850e\n", " | \n", "RUNNING | \n", "Jun 19, 2022 03:09:42.578 AM | \n", "- | \n", "