Quick start: Automate the lifecycle for a model with pipelines
Quick start: Automate the lifecycle for a model with pipelines You can create an end-to-end pipeline to deliver concise, pre-processed, and up-to-date data stored in an external data source. Read about Watson Pipelines, then watch a video and take a tutorial. Required services : Watson Studio : Watson Machine Learning Your basic workflow includes these tasks: 1. Open your sandbox project. Projects are where you can collaborate with others to work with data. 2. Add connections and data to the project. You can add CSV files or data from a remote data source through a connection. 3. Create a pipeline in the project. 4. Add nodes to the pipeline to perform tasks. 5. Run the pipeline and view the results. Read about pipelines The Watson Pipelines editor provides a graphical interface for orchestrating an end-to-end flow of assets from creation through deployment. Assemble and configure a pipeline to create, train, deploy, and update machine learning models and Python scripts. Putting a model into production is a multi-step process. Data must be loaded and processed, models must be trained and tuned before they are deployed and tested. Machine learning models require more observation, evaluation, and updating over time to avoid bias or drift. [Read more about pipelines](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/ml-orchestration-overview.html) [Learn about other ways to build models](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/data-science.html) Watch a video about pipelines ![Watch Video](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/lc-video.png) Watch this video to preview the steps in this tutorial. You might notice slight differences in the user interface that is shown in the video. The video is intended to be a companion to the written tutorial. This video provides a visual method to learn the concepts and tasks in this documentation. Try a tutorial to create a model with Pipelines This tutorial guides you through exploring and running an AI pipeline to build and deploy a model. The model predicts if a customer is likely subscribe to a term deposit based on a marketing campaign. In this tutorial, you will complete these tasks: * [Task 1: Open a project.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=enstep01) * [Task 2: Create a deployment space.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=enstep02) * [Task 3: Create the sample pipeline.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=enstep03) * [Task 4: Explore an existing pipeline.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=enstep04) * [Task 5: Run the pipeline.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=enstep05) * [Task 6: View the assets, deployed model, and online deployment.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=enstep06) This tutorial takes approximately 30 minutes to complete. Sample data The sample data that is used in the guided experience is UCI: Bank marketing data used to predict whether a customer enrolls in a marketing promotion. ![Spreadsheet of the Bank marketing data set](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/images/autoai_bank_sample_description.png) Expand all sections * Tips for completing this tutorial ### Use the video picture-in-picture Tip: Start the video, then as you scroll through the tutorial, the video moves to picture-in-picture mode. Close the video table of contents for the best experience with picture-in-picture. You can use picture-in-picture mode so you can follow the video as you complete the tasks in this tutorial. Click the timestamps for each task to follow along.The following animated image shows how to use the video picture-in-picture and table of contents features: ![How to use picture-in-picture and chapters](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/pip-and-chapters.gif){: width="560px" height="315px" data-tearsheet="this"} ### Get help in the community If you need help with this tutorial, you can ask a question or find an answer in the [Cloud Pak for Data Community discussion forum](https://community.ibm.com/community/user/cloudpakfordata/communities/community-home/digestviewer?communitykey=c0c16ff2-10ef-4b50-ae4c-57d769937235){: new_window}. ### Set up your browser windows For the optimal experience completing this tutorial, open Cloud Pak for Data in one browser window, and keep this tutorial page open in another browser window to switch easily between the two applications. Consider arranging the two browser windows side-by-side to make it easier to follow along. ![Side-by-side tutorial and UI](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/tutorial-side-by-side.png){: width="560px" height="315px" data-tearsheet="this"} Tip: If you encounter a guided tour while completing this tutorial in the user interface, click Maybe later. [Back to the top](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=envideo-preview) * Task 1: Open a project You need a project to store Prompt Lab assets. Watch a video to see how to create a sandbox project and associate a service. Then follow the steps to verify that you have an existing project or create a sandbox project. This video provides a visual method to learn the concepts and tasks in this documentation. 1. From the watsonx home screen, scroll to the Projects section. If you see any projects listed, then skip to [Task 2](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=enstep02). If you don't see any projects, then follow these steps to create a project. 1. Click Create a sandbox project. When the project is created, you will see the sandbox project in the Projects section. For more information or to watch a video, see [Creating a project](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/projects.html){: new_window}. \ ![Checkpoint icon](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/checkmark--filled-blue.svg){: iih} Check your progress The following image shows the home screen with the sandbox listed in the Projects section. You are now ready to open the Prompt Lab. ![Home screen with sandbox project listed.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/wx-home-screen.png){: width="100%" } [Back to the top](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-pipeline.html?context=cdpaas&locale=envideo-preview) * Task 2: Create a