Deep Learning: Language identification using Keras & TensorFlow

@tachyeonz : Source: openclipart.org, license: Public Domain

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Visualizing parts of Convolutional Neural Networks using Keras and Cats

@tachyeonz : It is well known that convolutional neural networks (CNNs or ConvNets) have been the source of many major breakthroughs in the field of Deep learning in the last few years, but they are rather unintuitive to reason about for most people.

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Deep Q Learning with Keras and Gym

@tachyeonz : This blog post will demonstrate how deep reinforcement learning (deep q learning) can be implemented and applied to play a CartPole game using Keras and Gym, in only 78 lines of code! I’ll explain everything without requiring any prerequisite knowledge about reinforcement learning.

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Fundamental Deep Learning code in TFLearn, Keras, Theano and TensorFlow

@tachyeonz : Yesterday evening, after years of attending the Open Statistical Programming Meetup in New York, I had the honour of giving a talk to the venerable institution on The Fundamentals of Deep Learning, replete with applications of the approach. My full slides from the evening are available here.

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Deep Learning Frameworks of 2017 Jan

@tachyeonz : Chainer is a deep learning framework that’s designed on the principle of define-by-run. Unlike frameworks that use the define-and-run approach, Chainer lets you modify networks during runtime, allowing you to use arbitrary control flow statements.

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Building powerful image classification models using very little data

@tachyeonz : In this tutorial, we will present a few simple yet effective methods that you can use to build a powerful image classifier, using only very few training examples –just a few hundred or thousand pictures from each class you want to be able to recognize.

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The Meta Model and Meta Meta-Model of Deep Learning

@tachyeonz : The model for deep learning consists of a computational graph that are most conveniently constructed by composing layers with other layers. Most introductory texts emphasize the individual neuron, but in practice it is the collective behavior of a layer of neurons that is important.

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Tags : computational graphs, deep learning, gan, keras, m, machine learning, meta models, mxnet, nervana, neural networks, object oriented design, tensorflow, uml, unified modeling language

Published On:December 25, 2016 at 01:01AM

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Develop Your First Neural Network in Python With Keras Step-By-Step

@tachyeonz : Keras is a powerful easy-to-use Python library for developing and evaluating deep learning models. It wraps the efficient numerical computation libraries Theano and TensorFlow and allows you to define and train neural network models in a few short lines of code.

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Tags : #ai, #analytics, #datascience, #deeplearning, #keras, #machinelearning, #python, m

Published On:December 05, 2016 at 06:35AM

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Keras Tutorial: The Ultimate Beginner’s Guide to Deep Learning in Python

@tachyeonz : In this step-by-step Keras tutorial, you’ll learn how to build a convolutional neural network in Python! In fact, we’ll be training a classifier for handwritten digits that boasts over 99% accuracy on the famous MNIST dataset.

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Tags : #deeplearning, #keras, #machinelearning, #python, #tutorials, m

Published On:November 27, 2016 at 08:08AM

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Text Generation With LSTM Recurrent Neural Networks in Python with Keras

@tachyeonz : Recurrent neural networks can also be used as generative models. This means that in addition to being used for predictive models (making predictions) they can learn the sequences of a problem and then generate entirely new plausible sequences for the problem domain.

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Tags : #analytics, #artificialintelligence, #datascience, #machinelearning, #neuralnetworks, #python, 3, keras, lstm, m

Published On:August 20, 2016 at 11:23PM

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Time Series Prediction With Deep Learning in Keras

@tachyeonz : Time Series prediction is a difficult problem both to frame and to address with machine learning. In this post you will discover how to develop neural network models for time series prediction in Python using the Keras deep learning library.

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Tags : #deeplearning, #keras, #timeseries, m

Published On:September 14, 2016 at 11:57PM

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Keras implementation of class activation mapping

@tachyeonz : This project implements class activation maps with Keras. Class activation maps are a simple technique to get the image regions relevant to a certain class.

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Tags : #keras, #neuralnetwork, #python, m

Published On:August 21, 2016 at 03:50AM

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