Tensorflow tutorials

Freeze Tensorflow models and serve on web

by Ankit Sachan • October 4, 2017

In this tutorial, we shall learn how to freeze a trained Tensorflow Model and serve it on a webserver. You can do this for any network you have trained but we shall use the trained model for dog/cat classification in this earlier tutorial and serve it on a python Flask webserver.  So you trained a new […]

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ResNet, AlexNet, VGGNet, Inception: Understanding various architectures of Convolutional Networks

by koustubh • August 9, 2017

Convolutional neural networks are fantastic for visual recognition tasks. Good ConvNets are beasts with millions of parameters and many hidden layers. In fact, a bad rule of thumb is: ‘higher the number of hidden layers, better the network’. AlexNet, VGG, Inception, ResNet are some of the popular networks. Why do these networks work so well? How are […]

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Image segmentation example image

Image Segmentation using deconvolution layer in Tensorflow

by koustubh • May 30, 2017

 In this series of post, we shall learn the algorithm for image segmentation and implementation of the same using Tensorflow. This is the first part of the series where we shall focus on understanding and be implementing a deconvolutional/fractional-strided-convolutional layer in Tensorflow.   Why is deconvolutional layer so important? Image segmentation is just one of […]

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Keras tensorflow tutorial

Keras tutorial: Practical guide from getting started to developing complex deep neural network

by Ankit Sachan • May 16, 2017

Keras is a high-level python API which can be used to quickly build and train neural networks using either Tensorflow or Theano as back-end. This tutorial assumes that you are slightly familiar convolutional neural networks. You can follow the first part of convolutional neural network tutorial to learn more about them. In this quick tutorial, we shall […]

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Deep Learning on Raspberry Pi

Accelerating Convolutional Neural Networks on Raspberry Pi

by koustubh • April 5, 2017

Unless you have been living under the rock, you must have heard of the revolution that deep learning and convolutional neural networks have brought in computer vision. Computers have achieved near-human level accuracy for most of the tasks. However, most of the top performing neural networks for state of the art image recognition problem suffer […]

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