Shows how to solve a problem on Kaggle with TF-Hub.
Explores text semantic similarity with the Universal Encoder Module.
Explores a generative image module.
Explores action recognition from video.
Exemplifies use of the DELF Module for landmark recognition and matching.
Explores object detection with the use of the Faster R-CNN module trained on Open Images v4.
This tutorial illustrates how to generate embeddings from a TF2 SavedModel given input data and build an approximate nearest neighbours (ANN) index using the extracted embeddings for real-time similarity matching and retrieval.
This tutorial illustrates how to generate embeddings from a model in the legacy TF1 Hub format given input data and build an approximate nearest neighbours (ANN) index using the extracted embeddings for real-time similarity matching and retrieval.
Shows how to train an image classifier based on any TensorFlow Hub module that computes image feature vectors.
Example tool to generate a text embedding module from a csv file with word embeddings.
Simple example of how to create a TensorFlow Hub Module.
Example tool to generate a text embedding module in TF2 format.
Example tool to train and export a simple MNIST classifier in TF2 format.