models/research/slim/nets/nasnet at master · tensorflow/models · GitHub

  • This directory contains the code for the NASNet-A model from the paper Learning Transferable Architectures for Scalable Image Recognition by Zoph et al.
  • One of the models is the NASNet-A built for CIFAR-10 and the other two are variants of NASNet-A trained on ImageNet, which are listed below.
  • Two NASNet-A checkpoints are available that have been trained on the ILSVRC-2012-CLS image classification dataset.
  • More information on integrating NASNet Models into your project can be found at the TF-Slim Image Classification Library.
  • To get started running models on-device go to TensorFlow Mobile.

models – Models and examples built with TensorFlow
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  • This is the code for my article “Coloring B&W portraits with neural networks” – – Earlier this year, Amir Avni used neural networks to troll the subreddit /r/Colorization.
  • For those who are not familiar, this subreddit is focused in “hand” coloring historical images using Photoshop.
  • Coloring images with neural networks creates some very interesting results.
  • Read the article to understand the context of the code.

Coloring-greyscale-images-in-Keras – Coloring B&W portraits with neural networks.
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Visualizing output of activation functions of CNNs: Comments  #DeepLearning #ML#AI

  • From Andrej Karpathy’s course cs231n:CNNs for Visual Recognition

    All the plots were generated with one full forward pass across all the layers of the network with the same activation function

    There are layers, each layer having units.

  • Random data points of training examples are generated from a univariate “normal” (Gaussian) distribution of mean and variance .
  • Weights for each layer were generated from the same distribution as that of but later on varied to obtain different plots.

DeepNets – How weight initialization affects forward and backward passes of a deep neural network
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scikit-learn-classifiers/sklearn-classifiers-tutorial.ipynb at master · mmmayo13/scikit-learn-classifiers · GitHub

Scikit-learn #MachineLearning classification algorithms - A quick overview with examples

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scikit-learn-classifiers – An introduction to implementing a number of scikit-learn classifiers, along with some data exploration
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Scripts to install and setup #Tensorflow and it's dependencies on #Ubuntu

  • Scripts to install and setup Tensorflow and it’s dependencies on Ubuntu.
  • to install everything in one command.
  • Scripts are included to install Java, Bazel, CUDA, Tensorflow and Docker.
  • Scripts can be used inside a docker container to install everything in one command or one at a time.

Tensorflow-setup-scripts – Scripts to install and setup Tensorflow and it’s dependencies on Ubuntu
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