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Keras Documentation

Keras: Theano-based Deep Learning library. Getting started: 30 seconds to Keras. Why this name, Keras? Keras: Theano-based Deep Learning library. Keras is a minimalist, highly modular neural network library in the spirit of Torch, written in Python, that uses Theano. Under the hood for optimized tensor manipulation on GPU and CPU. It was developed with a focus on enabling fast experimentation. Use Keras if you need a deep learning library that:. Runs seamlessly on CPU and GPU. New modules are dead simple...

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Keras Documentation | keras.io Reviews

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Keras: Theano-based Deep Learning library. Getting started: 30 seconds to Keras. Why this name, Keras? Keras: Theano-based Deep Learning library. Keras is a minimalist, highly modular neural network library in the spirit of Torch, written in Python, that uses Theano. Under the hood for optimized tensor manipulation on GPU and CPU. It was developed with a focus on enabling fast experimentation. Use Keras if you need a deep learning library that:. Runs seamlessly on CPU and GPU. New modules are dead simple...

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Keras Documentation | keras.io Reviews

https://keras.io

Keras: Theano-based Deep Learning library. Getting started: 30 seconds to Keras. Why this name, Keras? Keras: Theano-based Deep Learning library. Keras is a minimalist, highly modular neural network library in the spirit of Torch, written in Python, that uses Theano. Under the hood for optimized tensor manipulation on GPU and CPU. It was developed with a focus on enabling fast experimentation. Use Keras if you need a deep learning library that:. Runs seamlessly on CPU and GPU. New modules are dead simple...

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blog.keras.io

The Keras Blog

Is a Deep Learning library for Python, that is simple, modular, and extensible. Using pre-trained word embeddings in a Keras model. Sat 16 July 2016. In this tutorial, we will walk you through the process of solving a text classification problem using pre-trained word embeddings and a convolutional neural network. The full code for this tutorial is available on Github. What are word embeddings? Ideally, in a good embeddings space, the "path" (a vector) to go from "kitchen" and "dinner" would capture prec...

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keras.io

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Constraints - Keras Documentation

http://keras.io/constraints

Guide to the Sequential model. Guide to the Functional API. Writing your own Keras layers. Module allow setting constraints (eg. non-negativity) on network parameters during optimization. The penalties are applied on a per-layer basis. The exact API will depend on the layer, but the layers. Have a unified API. These layers expose 2 keyword arguments:. For the main weights matrix. From keras.constraints import maxnorm model.add(Dense(64, W constraint = maxnorm(2) ). Provided by Read the Docs.

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Convolutional Layers - Keras Documentation

http://keras.io/layers/convolutional

Guide to the Sequential model. Guide to the Functional API. Writing your own Keras layers. Keraslayers.convolutional.Convolution1D(nb filter, filter length, init='uniform', activation='linear', weights=None, border mode='valid', subsample length=1, W regularizer=None, b regularizer=None, activity regularizer=None, W constraint=None, b constraint=None, bias=True, input dim=None, input length=None). Int, e.g. 128 for sequences of 128-dimensional vectors), or. Name of activation function to use (see activat...

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Advanced Activations Layers - Keras Documentation

http://keras.io/layers/advanced_activations

Keraslayers.advanced activations.LeakyReLU(alpha=0.3). Special version of a Rectified Linear Unit that allows a small gradient when the unit is not active:. F(x) = alpha*x for x 0. Arbitrary. Use the keyword argument. Tuple of integers, does not include the samples axis) when using this layer as the first layer in a model. Same shape as the input. Float = 0. Negative slope coefficient. Keraslayers.advanced activations.PReLU(init='zero', weights=None). Arbitrary. Use the keyword argument. Float Initial va...

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Recurrent Layers - Keras Documentation

http://keras.io/layers/recurrent

Guide to the Sequential model. Guide to the Functional API. Writing your own Keras layers. Keraslayers.recurrent.Recurrent(weights=None, return sequences=False, go backwards=False, stateful=False, unroll=False, consume less='cpu', input dim=None, input length=None). Abstract base class for recurrent layers. Do not use in a model - it's not a valid layer! Use its children classes. All recurrent layers (. Also follow the specifications of this class and accept the keyword arguments listed below. Boolean (d...

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Datasets - Keras Documentation

http://keras.io/datasets

Guide to the Sequential model. Guide to the Functional API. Writing your own Keras layers. CIFAR10 small image classification. CIFAR100 small image classification. IMDB Movie reviews sentiment classification. Reuters newswire topics classification. MNIST database of handwritten digits. CIFAR10 small image classification. Dataset of 50,000 32x32 color training images, labeled over 10 categories, and 10,000 test images. X train, X test. Uint8 array of RGB image data with shape (nb samples, 3, 32, 32).

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Deep Learning Frameworks Overview – Grzegorz Gwardys

https://grzegorzgwardys.wordpress.com/2016/03/29/deep-learning-frameworks-overview

Experience with Machine/Deep Learning and more …. Deep Learning Frameworks Overview. March 29, 2016. May 7, 2016. I have some experience with caffe. And it was my main tool for research in area of Music Information Retrieval. However, Deep Learning is not reduced to Convolution Neural Networks and caffe. Is not suitable for fast, prototype implementations. So I was faced with the question: What is the best Deep Learning framework? By the time research has moved ahead. However, both question and answers d...

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Analyzing Six Deep Learning Tools for Music Generation - The Asimov Institute

http://www.asimovinstitute.org/analyzing-deep-learning-tools-music

Analyzing Six Deep Learning Tools for Music Generation. October 5, 2016. October 7, 2016. Magenta is Google’s open source deep learning music project. They aim to use machine learning to generate compelling music. The project went open source in June 2016 and currently implements a regular RNN. And two LSTM’s. The piece below is generated by Magenta from the 8th note onward. Here they use their attention model with the provided pre-trained bundle. While it can handle chords, it converts the jazz midi to ...

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My Dive into Deep Learning | W Christian Consulting

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What could you be doing better? Build Your Business Online! William A. Christian, Jr., Ph.D. (Resume). My Dive into Deep Learning. Over-)Simplified view of a deep learning architecture for classifying documents. 80% Classification Accuracy in 10 Minutes. Several tools were described, but we all seemed to flock toward Keras. For building and manipulating our neural networks. Written in python, it is a fast-prototyping library that sits on top of another python library called Theano. Installing Keras wasn&...

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CodeBook Archives - A Blog From Human-engineer-being

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A Blog From Human-engineer-being. Brief History of Machine Learning. Duplicate Question Detection with Deep Learning on Quora Dataset. February 12, 2017. Quora recently announced the first public dataset. That they ever released. It includes 404351 question pairs with a label column indicating if they are duplicate or not. In this post, I like to investigate this dataset and at least propose a baseline method with deep learning. There are two other columns "q1id" and "q2id" but I really do not know how t...

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从Theano到Lasagne：基于Python的深度学习的框架和库 - Python - 伯乐在线

http://python.jobbole.com/81896

2015/08/07 · 工具与框架. 最近，深度神经网络以 Deep Dreams 形式在网站中如雨后春笋般出现，或是像谷歌研究原创论文中描述的那样 Inceptionism。主页 http:/ deeplearning.net/software/theano/. Github网址 https:/ github.com/Theano/Theano. 主页 http:/ deeplearning.net/software/pylearn2/. Github网址 https:/ github.com/lisa-lab/pylearn2. Github网址 https:/ github.com/mila-udem/blocks. 主页 http:/ keras.io/. Github网址 https:/ github.com/fchollet/keras. Github网址 https:/ github.com/Lasagne/Lasagne. 重点遵循Unix哲学做一件事，并把它做好，重点集中在前馈神经网络。深度学习 ( Deep Learning ) 的 Python 包哪家强.

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CODE BOOK - A Blog From Human-engineer-being

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A Blog From Human-engineer-being. Brief History of Machine Learning. Duplicate Question Detection with Deep Learning on Quora Dataset. Quora recently announced the first public dataset. That they ever released. It includes 404351 question pairs with a label column indicating if they are duplicate or not. In this post, I like to investigate this dataset and at least propose a baseline method with deep learning. There are two other columns "q1id" and "q2id" but I really do not know how they are useful sinc...

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Tips & Tricks Archives - A Blog From Human-engineer-being

http://www.erogol.com/category/tips-tricks

A Blog From Human-engineer-being. Brief History of Machine Learning. Category Archives: Tips and Tricks. Duplicate Question Detection with Deep Learning on Quora Dataset. February 12, 2017. Quora recently announced the first public dataset. That they ever released. It includes 404351 question pairs with a label column indicating if they are duplicate or not. In this post, I like to investigate this dataset and at least propose a baseline method with deep learning. There are two other columns "q1id" and "...

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Keras Documentation

Keras: Theano-based Deep Learning library. Getting started: 30 seconds to Keras. Why this name, Keras? Keras: Theano-based Deep Learning library. Keras is a minimalist, highly modular neural network library in the spirit of Torch, written in Python, that uses Theano. Under the hood for optimized tensor manipulation on GPU and CPU. It was developed with a focus on enabling fast experimentation. Use Keras if you need a deep learning library that:. Runs seamlessly on CPU and GPU. New modules are dead simple...

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