Deep Learning Fast and Easy

Why FastEstimator?

FastEstimator is a high-level open source deep learning framework that can help you build complex deep learning systems easily. It provides all the simplicity and flexibility needed to build a high-performance deep learning model and run it anywhere.


Built upon TensorFlow2 and PyTorch, FastEstimator combines the best of the two. Enjoy both speed and flexibility!


You only need to know 3 modular APIs to get started. Use your favorite backend for customization, no extra learning is needed.

Yet Flexible!

We introduce new concepts of of AI modularization: Operator & Trace, which can help you implement your crazy ideas without friction.

Easy to scale

Multi-GPU training requires no efforts on your side. Just run the code on multi-GPU system and we will scale it for you!

Pre-bundled Power

FastEstimator provides ready-made AI modular components to make prototyping easier. Plug them in your own applications!

Application Hub, not model zoo

We offer end-to-end workflows of State-Of-The-Art across different AI domains. Come learn with us and use them for your own project!

How does FastEstimator work?

All deep learning training workflows involve three essential components: data pipeline, network, and optimization strategy. Each one represents a critical API in FastEstimator:


Pipeline takes care of loading and preprocessing data


Network compiles all trainable and differentiable model operations.


Estimator manages the training loop.

Our Application hub

FastEstimator does not only provide a model zoo, but end-to-end implementation examples of state-of-the-art models. Every template has step-by-step instructions to ensure you can easily build new AI applications using your own data.

Handwritten Digit Classification LeNet, MNIST dataset
Train a LeNet neural network to classify MNIST handwritten digital number.
Lung X-ray Image Segmentation Unet, Montgomery dataset
Train a neural network to label the region of patient lung from a X-ray images.
Fast Style Transfer Modified ResNet, COCO2014 dataset
Train a neural network that applies art style on any target image