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.
This project demonstrates the use of various pre-trained models for transfer learning in NLP using TensorFlow Hub.
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
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
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.
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.
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.
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.
Part of engineering thesis. Serving Tensorflow Hub's model with FastAPI
Tutorial sobre transferência de aprendizado utilizando Tensorflow Hub apresentado no IV Meetup PyData Manaus
Image classifier application to classify flowers to 102 categories, using TnensorFlow hub and Conv2D
Uses Transfer Learning to create an advanced and more accurate Machine Learning model for classifying type of flowers in the flower dataset
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