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AutoML Video Classification Example
The objective of this notebook is to build a AutoML Video Classification Model.
The steps performed include the following:
- Set your task name, and GCS prefix
- Copy AutoML video demo train data for creating managed dataset
- Create a dataset on Vertex AI.
- Configure a training job
- Launch a training job and create a model on Vertex AI
- Copy AutoML Video Demo Prediction Data for creating batch prediction job
- Perform batch prediction job on the model
Learn more about Classification for video data.
Custom training using Python package, managed text dataset, and TF Serving container
Learn how to create a Custom Model using Custom Python Package Training and you learn how to serve the model using TensorFlow-Serving Container for online prediction.
The steps performed include:
- Create utility functions to download data and prepare csv files for creating Vertex AI Managed Dataset
- Download Data
- Prepare CSV Files for Creating Managed Dataset
- Create Custom Training Python Package
- Create TensorFlow Serving Container
- Run Custom Python Package Training with Managed Text Dataset
- Deploy a Model and Create an Endpoint on Vertex AI
- Predict on the Endpoint
- Create a Batch Prediction Job on the Model
Learn more about Custom training.
Train a pytorch model with Vertex AI SDK 2.0 and Bigframes
Learn to use `Vertex AI SDK 2.
The steps performed include:
- Initialize a dataframe from a BigQuery table and split the dataset
- Perform transformations as a Vertex AI remote training.
- Train the model remotely and evaluate the model locally
Learn more about bigframes.
Train a scikit-learn model with Vertex AI SDK 2.0 and Bigframes
Learn to use `Vertex AI SDK 2.
The steps performed include:
- Initialize a dataframe from a BigQuery table and split the dataset
- Perform transformations as a Vertex AI remote training.
- Train the model remotely and evaluate the model locally
Learn more about bigframes.
Train a Tensorflow Keras model with Vertex AI SDK 2.0 and Bigframes
Learn to use `Vertex AI SDK 2.
The steps performed include:
- Initialize a dataframe from a BigQuery table and split the dataset
- Perform transformations as a Vertex AI remote training.
- Train the model remotely and evaluate the model locally
Learn more about bigframes.