This project builds end-to-end multiclass Classification of dog breeds.
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Updated
Aug 14, 2020 - Jupyter Notebook
This project builds end-to-end multiclass Classification of dog breeds.
Basics of machine learning is END-TO-END Repository which includes very Basic Machine Learning Models and Notebook
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
Apply style transfer on 2 different CSU East Bay campus images, using 2 different painting styles
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.
In this repository, I am implementing transfer learning with TensorFlow Hub for the detection of toxic content among Quera questions.
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.
Part of engineering thesis. Serving Tensorflow Hub's model with FastAPI
Image classifier application to classify flowers to 102 categories, using TnensorFlow hub and Conv2D
Artnet is a social network based on sharing artworks
Submodule of project Plantify with TensorFlow Hub
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.
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.
Text analysis with NLP Tool kit basics and Preprocessing the text using Tensorflow built-in models
Uses Transfer Learning to create an advanced and more accurate Machine Learning model for classifying type of flowers in the flower dataset
Build a simple text classifier with TF-Hub
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.
A website with complete cloud integration that utilizes terraform and dockers for deployment to use an image to predict the location in Asia.
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