Build Low Code Automated Tensorflow explainable models in just 3 lines of code. Library created by: Hasan Rafiq - https://www.linkedin.com/in/sam04/
A fluent API layer for tensorflow extended e2e machine learning pipelines
Code for creating end-end TFX production pipeline for GPT-2.
An example of TFX intended to work with Vertex AI in Google Cloud
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.
This is an example of what a TFX pipeline would look like when used for NLP
A sample program for image classification model using TFX.
A TFX implementation of the paper on transformers, Attention is All You Need
🌱 Pipeline Implementation using TFX for Plant Disease Detection Model. The Repository includes the keras model code, pipeline implementation for local Deployment & Airflow Noteebooks, a Minimalistic Client for testing the model after Serving it (TFX Serving REST-API), and a Simple Proxy Server.
Personal project aimed at developing a ML service which resembles a production environment system
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.
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