tfx

PipelineAI Kubeflow Distribution

A guideline for building practical production-level deep learning systems to be deployed in real world applications.

NitroML is a modular, portable, and scalable model-quality benchmarking framework for Machine Learning and Automated Machine Learning (AutoML) pipelines.

TFX-Addons is a collection of community projects to build new components, examples, libraries, and tools for TFX. The projects are organized under the auspices of the special interest group, SIG TFX-Addons. Join the group at http://goo.gle/tfx-addons-group

End-to-end pipeline with TFX to train and deploy a BERT model for sentiment analysis.

Kubeflow pipelines built on top of Tensorflow TFX library

A fluent API layer for tensorflow extended e2e machine learning pipelines

TangoFX Sessions is a plug and play platform for Internet calling. It not only makes video call over internet but also provides us the ability to use immensely interactive tools with our communication for example features such as creating drawing or writing code together while in a video call.

Code for creating end-end TFX production pipeline for GPT-2.

Machine Learning with TensorFlow Extended (TFX) Pipelines

Using pachyderm as pipeline engine to serve "taxi chicago" machine learning models

Assignments of "Machine Learning Engineering for Production (MLOps) Specialization" by Coursera (https://www.coursera.org/specializations/machine-learning-engineering-for-production-mlops)

Collection of components for TFX

A sample program for image classification model using TFX.

deeplearning.ai Course Materials

Building end-to-end production grade machine learning pipelines.

Verification of the 2018 TFX Qualifier Competition Leaderboard

TFX is an end-to-end platform for deploying production ML pipelines