Скачать или смотреть Streamlining Wildlife Image Classification in BigQuery with an Imported Model GSP1248

Overview
In this lab, you learn how to help streamline an image classification workflow in BigQuery using an imported model (PyTorch model created in ONNX format), and Google SQL queries.

As a new Data Analyst at Cymbal Media and Entertainment, you have been tasked to experiment with an imported model and BigQuery Machine Learning for inference to classify wildlife images. This project aims to automate the image classification process, simplify content creation, and potentially build a larger database of wildlife images for future content on Cymbal's streaming platform.

ONNX is an open format built to represent machine learning models. ONNX defines a common set of operators - the building blocks of machine learning and deep learning models - and a common file format to enable AI developers to use models with a variety of frameworks, tools, runtimes, and compilers.

BigQuery is a fully managed, AI-ready data analytics platform which helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud. One of its key features is BigQuery Machine Learning for inference, which lets you create and run machine learning (ML) models by using GoogleSQL queries.

Running ML models using GoogleSQL Queries
Usually, performing ML or AI on large datasets requires extensive programming and knowledge of ML frameworks. This restricts solution development to a small set of people within each company, and excludes data analysts who understand the data but have limited ML knowledge and programming expertise. However, with BigQuery ML, SQL practitioners can use existing SQL knowledge, skills and tools to build and to generate results from models built with ONNX, and stored in a cloud storage bucket. This helps companies with model choice, and flexibility from an MLOPs perspective. It also helps to scale their ML initiatives.

The image dataset
The images used in this lab are from the Animals Detection Images Dataset on Kaggle.

Objectives
In this lab, you learn how to:
Create a cloud resource connection.
Grant permissions to the connection's service account.
Create a BigQuery dataset and tables,
Import the ONNX model into BigQuery.
Classify images using the imported model.
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