This projects uses Convolutional Neural Networks to classify images , CIFAR data set is used
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Updated
May 21, 2017 - HTML
This projects uses Convolutional Neural Networks to classify images , CIFAR data set is used
Exploration and implementation of an inverse image search using transfer learning and nearest neighbors search.
Repository to benchmark the performance of Cloud CPUs vs. Cloud GPUs on TensorFlow, FloydHub, AWS and soon GCE.
An Application that Detects Hand-Drawn Digits using a Convolutional Neural Network
Code used to build an image classifier for the Fashion MNIST dataset. Built using the Keras library and trained on the FloydHub cloud platform
Chicago Skyline Towers Detection using Tensorflow Object Detection!
Exploration of different pre-trained models to make predictions on Flickr images.
Example end-to-end Keras training and serving
Deep Learning Nanodegree Foundation (Feb-May 2017)
Contains data, notebooks and other files of FloydHub's mini-series on machine learning project structuring, model debugging, various tips and tricks and more
It uses Conditional GAN(Generative adversarial networks) to convert a front face image into a more primitive representation of the face.
udacity dlnd image classification for CIFAR-10
🎓 Generate your own commencement address with Markov chains
This repository provides a helper class to keep track of metrics such as loss or accuracy when training your deep learning model and deploying it to floydhub servers
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