Blog Archives

RNN made easy with MXNet R

October 10, 2017
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RNN made easy with MXNet R

This tutorial presents an example of application of RNN to text classification using padded and bucketed data to efficiently handle sequences of varying lengths. Some functionalities require running on a GPU with CUDA. Example based on sentiment analy...

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Conditional Generative Adversial Network with MXNet R package

May 31, 2017
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Conditional Generative Adversial Network with MXNet R package

This tutorial shows how to build and train a Conditional Generative Adversial Network (CGAN) on MNIST images. How GAN works A Generative Adversial Model simultaneously trains two models: a generator that learns to output fake samples from an unknown ...

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Conditional Generative Adversarial Network with MXNet R package

May 31, 2017
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Conditional Generative Adversarial Network with MXNet R package

This tutorial shows how to build and train a Conditional Generative Adversarial Network (CGAN) on MNIST images. How GAN works A Generative Adversarial Model simultaneously trains two models: a generator that learns to output fake samples from an unkn...

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MinPy: The NumPy Interface upon MXNet’s Backend

January 17, 2017
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MinPy: The NumPy Interface upon MXNet’s Backend

Machine learning is now enjoying its golden age. In the past few years, its effectiveness has been proved by solving many traditionally hard problems in computer vision and natural language processing. At the same time, different machine learning frameworks came out to justify different needs. These frameworks, fall generally into two different categories: symbolic programming and imperative programming. Symbolic V.S....

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GPU Accelerated XGBoost

December 13, 2016
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GPU Accelerated XGBoost

GPU Accelerated XGBoost Decision tree learning and gradient boosting have until recently been the domain of multicore CPUs. Here we showcase a new plugin providing GPU acceleration for the XGBoost library. The plugin provides significant speedups over multicore CPUs for large datasets. The plugin can be found at: https://github.com/dmlc/xgboost/tree/master/plugin/updater_gpu Before talking about the GPU plugin we briefly explain the XGBoost algorithm. XGBoost for classification...

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Fusion and Runtime Compilation for NNVM and TinyFlow

November 20, 2016
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Fusion and Runtime Compilation for NNVM and TinyFlow

Fusion and Runtime Compilation Today’s deep learning models perform tens of thousands of operations on GPU. The input and output of each GPU kernel has to be stored in the global memory, but read and write on global memory is much slower than on on-chip register. When some special kernels executed in sequence share some data, performance and memory locality...

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A Full Integration of XGBoost and Apache Spark

October 26, 2016
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A Full Integration of XGBoost and Apache Spark

Introduction On March 2016, we released the first version of XGBoost4J, which is a set of packages providing Java/Scala interfaces of XGBoost and the integration with prevalent JVM-based distributed data processing platforms, like Spark/Flink. The integrations with Spark/Flink, a.k.a. XGBoost4J-Spark and XGBoost-Flink, receive the tremendous positive feedbacks from the community. It enables users to build a unified pipeline, embedding ...

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Build your own TensorFlow with NNVM and Torch

September 29, 2016
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Build your own TensorFlow with NNVM and Torch

TL;DR Do something fun, How about build your own TensorFlow with NNVM and Torch7 This is a new interesting era of deep learning, with emergence trend of new system, hardware and computational model. The usecase for deep learning is more heterogeneous,...

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Build your own TensorFlow with NNVM and Torch

September 29, 2016
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TL;DR Do something fun, How about build your own TensorFlow with NNVM and Torch7 This is a new interesting era of deep learning, with emergence trend of new system, hardware and computational model. The usecase for deep learning is more heterogeneous,...

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Recurrent Models and Examples with MXNetR

August 18, 2016
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As a new lightweight and flexible deep learning platform, MXNet provides a portable backend, which can be called from R side. MXNetR is an R package that provide R users with fast GPU computation and state-of-art deep learning models. In this post, We...

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