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A guideline for building practical production-level deep learning systems to be deployed in real world applications.
An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI
Build Low Code Automated Tensorflow explainable models in just 3 lines of code. Library created by: Hasan Rafiq - https://www.linkedin.com/in/sam04/
Developers helping developers. 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
Machine Learning Pipeline for Semantic Segmentation with TensorFlow Extended (TFX) and various GCP products
NitroML is a modular, portable, and scalable model-quality benchmarking framework for Machine Learning and Automated Machine Learning (AutoML) pipelines.
End-to-end pipeline with TFX to train and deploy a BERT model for sentiment analysis.
Project demonstrating dual model deployment scenarios using Vertex AI (GCP).
https://blog.tensorflow.org/2021/12/continuous-adaptation-for-machine.html
Assignments of "Machine Learning Engineering for Production (MLOps) Specialization" by Coursera (https://www.coursera.org/specializations/machine-learning-engineering-for-production-mlops)
Kubeflow pipelines built on top of Tensorflow TFX library
Machine Learning with TensorFlow Extended (TFX) Pipelines
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.
The TFX Automation Bot is a cutting-edge Python-based tool designed to streamline machine learning pipelines and optimize TensorFlow Extended (TFX) workflows. This bot automates model training, validation, deployment, and monitoring, making AI development seamless and efficient.
This repository contains code to train, export and serve a Tensorflow model with TFServing. Additionally, this repository provides the installation and configuration of TFServing through a Docker image.