Generic and easy-to-use serving service for machine learning models
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Updated
Jan 3, 2021 - JavaScript
Generic and easy-to-use serving service for machine learning models
A tutorial of building tensorflow serving service from scratch
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.
Lightweight tool that generates Go structures and Tensorflow inference execution code from SavedModel
Merging Models for TensorFlow Serving HOT UPDATING
Our Little Tools
Example how to deploy your TensorFlow model in production using the Tensorflow-serving
Fire Detection TFOD 2.0
Image classification project using machine learning, CNN, and transfer learning. Includes model training and deployment examples with TensorFlow Lite (TFLite), TensorFlow SavedModel, and TensorFlow.js (TFJS). This repository provides scripts, models, and deployment guides for easy integration.
text classification, text to emotions notebook 🎨
Demo on performing multiclass image classification using Convolutional Neural Network (CNN) in Tensorflow 2. Techniques such as earlystopping, batchnormalizing and dropout are explored to prevent overfitting
Angular webapp to demo minst-cnn inference
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