AI Platform Training brings the power and flexibility of TensorFlow, scikit-learn, XGBoost, and custom containers to the cloud. You can use AI Platform Training to train your machine learning models using the resources of Google Cloud.
Getting started
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Introduction to AI Platform
An overview of AI Platform products.
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Training overview
An introduction to training machine learning models on AI Platform Training.
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Development environment
Requirements for your local development environment.
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Training with TensorFlow 2
Details about training with TensorFlow 2.
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Getting started: training and prediction with TensorFlow Keras
Train a TensorFlow Keras model in AI Platform Training and deploy the model to AI Platform Prediction.
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Getting started: training and prediction with TensorFlow Estimator
Train a TensorFlow Estimator model in AI Platform Training and deploy the model to AI Platform Prediction.
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Getting started with scikit-learn and XGBoost
Train a scikit-learn or XGBoost model.
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Getting started with custom containers
Train a PyTorch model by using a custom container.
Training workflow
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Packaging a training application
Package your Python training code to make it compatible with AI Platform Training.
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Running a training job
Run a training job.
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Specifying machine types or scale tiers
Configure which types of virtual machines your training job uses.
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Monitoring training jobs
Monitor the status of your training jobs with logs and resource utilization metrics.
Training at scale
Hyperparameter tuning
Accelerators
Custom containers
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Overview of containers
An introduction to how you can customize your training jobs by providing your own Docker container.
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Training with containers on AI Platform
Create a custom Docker container and use it to run a training job.
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Distributed training with containers
Configure a custom container job to use multiple virtual machines.
Integrating with tools and services
Monitoring and security
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Viewing audit logs
Monitor admin activity and data access with Cloud Audit Logs.
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Access control
An overview of permissions required to perform various actions in the AI Platform Training and Prediction API, as well as IAM roles that provide these permissions.
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Training with a custom service account
Use a custom service account for your training application
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Using VPC Service Controls with Training
Mitigate the risk of data exfiltration by using a service perimeter.
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Using customer-managed encryption keys (CMEK)
Encrypt training job data with customer-managed encryption keys.
AI Platform Training resources
Tutorials
Runtime versions
AI Platform built-in algorithms
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Introduction to built-in algorithms
An overview of built-in algorithms.
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Preprocessing data for tabular built-in algorithms
Use automatic preprocessing to prepare your data for training.
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Getting started with the linear learner algorithm
Train a model with the built-in TensorFlow linear learner algorithm.
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Training using the built-in linear learner algorithm
Customize how you use the built-in linear learner algorithm for training.
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Linear learner algorithm reference
Configuration options for the built-in linear learner algorithm.
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Getting started with the wide and deep algorithm
Train a model with the built-in TensorFlow wide and deep algorithm.
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Training using the built-in wide and deep algorithm
Customize how you use the built-in wide and deep algorithm for training.
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Wide and deep algorithm reference
Configuration options for the built-in wide and deep algorithm.
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Getting started with the XGBoost algorithm
Train a model with the built-in XGBoost algorithm.
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Training using the built-in XGBoost algorithm
Customize how you use the built-in XGBoost algorithm for training.
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Training using the built-in distributed XGBoost algorithm
Customize how you use the distributed version of the built-in XGBoost algorithm.
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XGBoost algorithm reference
Configuration options for the built-in XGBoost algorithm.
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Getting started with the image classification algorithm
Train a model with the built-in image classification algorithm.
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Training using the built-in image classification algorithm
Customize how you use the built-in image classification algorithm for training.
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Image classification algorithm reference
Configuration optionsfor the built-in image classification algorithm.
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Getting started with the image object detection algorithm
Train with the built-in image object detection algorithm.
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Training using the built-in image object detection algorithm
Customize how you use the built-in image object detection algorithm for training.
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Image object detection algorithm reference
Configuration options for the built-in image object detection algorithm.