Using TFHub Modules for Classification
-
Updated
Apr 22, 2018 - Jupyter Notebook
Using TFHub Modules for Classification
Build a simple text classifier with TF-Hub
Export and optimize Tensorflow Hub models for inference and deployment
A tensorflow.js wrapper for ESRGAN based on the ESRGAN paper. Zoom and enhance like they do in the movies with nodeJS!
classification and segmentation of retinal scans
Using pre-trained models to create crude object detection models
Detect Landmarks similar to Google Lens using TensorFlow Hub
A repo to Fine Tune BERT and use it for text classification.
MIRNet model is used to enhance a low-light image. Implemented MIR-Net model with TF-Lite.
Build and fine-tune your Image Classifier using a Vision Transformer Model from TensorFlow Hub
Conversion of TF-Lite model from ZERO-DCE model
Find closest matches of text content based on embeddings from neural networks
An awesome list of TensorFlow Lite models, samples, tutorials, tools and learning resources.
Presents an optimized Apache Beam pipeline for generating sentence embeddings (runnable on Cloud Dataflow).
MobileNet V2 Transfer Learning with TensorFlow.js
American Sign Language Detection is a deep learning end to end project where we can detect American Sign Language.
Multiclass Intent Classification using MLP, LSTM, and BERT (subtask: Topic Modelling).
Used Tensorflow and Keras Framework
Add a description, image, and links to the tfhub topic page so that developers can more easily learn about it.
To associate your repository with the tfhub topic, visit your repo's landing page and select "manage topics."