Category: cloud
-
Train a PyTorch Model with Sample Data
Okay, here’s a sample dataset for a house price prediction model, incorporating many of the features we discussed. This data is synthetic and intended to illustrate the variety of features. Code snippet Explanation of the Columns: How to Use This Data in Vertex AI: Remember that this is just a small sample. For a real-world… Read more
-
Deploying a PyTorch model on Vertex AI
Deploying a PyTorch model on Vertex AI involves several steps. Here’s a breakdown: 1. Prerequisites: 2. Steps Here’s a conceptual outline with code snippets using the Vertex AI Python SDK: 2.1 Upload Model Artifacts First, upload your trained model (house_price_model.pth) and preprocessor to your GCS bucket. 2.2 Create a Serving Container Since you’re using PyTorch,… Read more
-
Call Vertex AI endpoint
To call your Vertex AI endpoint using HTTP, you’ll need to construct a POST request with the correct authorization and data format. Here’s a breakdown and an example using curl: 1. Prerequisites 2. Authorization Vertex AI API requests require an authorization header with a valid access token. If you have the Google Cloud SDK installed,… Read more