Keras + Universal Sentence Encoder = Transfer Learning for text data
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Updated
Sep 27, 2018 - Jupyter Notebook
Keras + Universal Sentence Encoder = Transfer Learning for text data
Landmark Detection (Google Lens like Interface) using TensorFlow Hub & Gradio
Build a simple text classifier with TF-Hub
Build an image classifier using transfer learning
Who's a good dog? Who likes ear scratches? Well, it seems those fancy deep neural networks don't have all the answers. However, maybe they can answer that ubiquitous question we all ask when meeting a four-legged stranger: what kind of good pup is that? This notebook builds a multi-class image classifier using TensorFlow 2.0 and TensorFlow Hub.
A website with complete cloud integration that utilizes terraform and dockers for deployment to use an image to predict the location in Asia.
This project builds end-to-end multiclass Classification of dog breeds.
Essa é uma aplicação que utiliza os classificadores do tensor hub e o Tensorflow JS para a criação de uma extensão chrome que filtre toda imagens.
A performance comparison of sentiment analysis between pre-trained NLP models and visualization them in TensorBoard . Fine tuning some model to for more accurate prediction.
Basics of machine learning is END-TO-END Repository which includes very Basic Machine Learning Models and Notebook
Image Scene Classification Model for TensorFlow Hub
This is repo is in development. It is used to keep resources, course references, and code examples while preparing for the TensorFlow Developer Certification exam. If the work here helps you in some way please feel free to share, fork, or star.
The comparison between different embeddings (TF-IDF, USE, and TF-IDF + USE) and various classifiers provides valuable insights into the performance of different techniques for sentiment classification.
A Machine Learning model that predicts the breed of a dog given it's image
Text analysis with NLP Tool kit basics and Preprocessing the text using Tensorflow built-in models
It detects whether entered questions are similar or not
Fake News Headlines Detection using different NLP strategies: BOW, FastText Embedding, Transformers.
Develop an image classification model to distinguish between images of cats and dogs using data science techniques in Python.
Apply style transfer on 2 different CSU East Bay campus images, using 2 different painting styles
In this repository, I am implementing transfer learning with TensorFlow Hub for the detection of toxic content among Quera questions.
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