Category: Components of TFX
Pipeline – Pipelines using Kubeflow for Custom Models
Follow these steps to analyze the status of the pipeline job, artifacts, lineage and output: Step 1: Pipeline of custom model Open the link as shown in Figure 7.10 to navigate to the pipelines of Vertex AI. The pipeline will start executing and will take about 5 to 10 mins. All the four tasks in
Pipeline code walk through – Pipelines using Kubeflow for Custom Models
We will be using Python 3 notebook file to type commands, create a pipeline, compile and to run it. Follow the following mentioned steps to create a Python file and type the Python codes given in this section. Step 1: Create Python notebook file Once the workbench is created, open the Jupyterlab and follow the
Additional permissions – Pipelines using Kubeflow for Custom Models
We also need to grant additional permission to the service account associated with the compute engine of GCP since we are fetching data from BigQuery. Follow these steps to grant the required permission. Step 1: Open IAM and admin section Follow the steps mentioned in Figure 7.2 to add roles to the service account associated
Data for model training – Pipelines using Kubeflow for Custom Models
Introduction In the previous chapter, we worked on the pipelines of GCP using Kubeflow. We built the first pipeline using AutoML of the platform for model training. In this chapter, we will see how to build pipelines for custom models and compare the results of different pipelines. We will also understand a few differences between
Submitting training job with Python SDK – Vertex AI Custom Model Hyperparameter and Deployment
In all the exercises that we have covered in the previous chapters, we have mainly worked on graphical user interface of the platform. Let us now see how to submit the job for training using Python code.Step 1: Create a new python notebook on the Jupyter labFollow the given steps to create a new Python
Completion of custom model training job – Vertex AI Custom Model Hyperparameter and Deployment
Based on the complexity of the model, model training might take anywhere between a few minutes to a few hours. Once the model training is completed, it will be listed under the training section, as shown in the Figure 5.18: Figure 5.18: Custom job listed under training module of Vertex AI Training job will be