GoogleCloudPlatform/tf-estimator-tutorials

This repository includes tutorials on how to use the TensorFlow estimator APIs to perform various ML tasks, in a systematic and standardised way

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This project offers practical, step-by-step guides for machine learning practitioners and data scientists to build, train, and evaluate various machine learning models using TensorFlow's Estimator API. It demonstrates how to handle different data types and prepare them for tasks like classification, regression, and time-series analysis. You'll learn to input raw data (like CSVs or TFRecords) and get out trained, evaluated, and ready-to-deploy machine learning models.

671 stars.

Use this if you are a data scientist or ML engineer looking for standardized, systematic examples to implement machine learning models with TensorFlow's Estimator API, especially if you need to perform diverse tasks like classification, regression, or time-series analysis.

Not ideal if you are looking for a simple, no-code solution or if your primary focus is on other machine learning frameworks outside of TensorFlow Estimators.

Machine Learning Engineering Data Science Workflow Predictive Modeling Statistical Learning Model Deployment
No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

671

Forks

230

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Mar 12, 2026

Commits (30d)

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