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Enterprise-ready Tool Support for Apache Camel | Javalobby

Enterprise-ready Tool Support for Apache Camel | Javalobby | EEDSP | Scoop.it
Apache Camel is my favorite integration framework on the Java
platform due to great DSLs, a huge community, and so many different
components. Camel is used...
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EEDSP
Digital Signal Processing, Data Analytics, Big Data, HPC, Deep Learning, GPGPU, Distributed and Parallel Computing
Curated by Shiwon Cho
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Deep Neural Network from scratch

Deep Neural Network from scratch | EEDSP | Scoop.it
In this blog post you will learn how a neural network works. All the parts are explained, including the maths. You will also find a python implementation using numpy and a second one using TensorFlow.
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Emotional chatting machine assesses your emotion and copies it

Emotional chatting machine assesses your emotion and copies it | EEDSP | Scoop.it
Chatbots have never been able to empathize. That looks set to change, thanks to a Chinese team that has built a chatbot capable of conveying specific emotions.
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A Brief History of CNNs in Image Segmentation: From R-CNN to Mask R-CNN

A Brief History of CNNs in Image Segmentation: From R-CNN to Mask R-CNN | EEDSP | Scoop.it
At Athelas, we use Convolutional Neural Networks(CNNs) for a lot more than just classification! In this post, we’ll see how CNNs can be used, with great results, in image instance segmentation. Ever…
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A news-analysis NeuralNet learns from a language NeuralNet

A news-analysis NeuralNet learns from a language NeuralNet | EEDSP | Scoop.it
A common way to solve a complex computing task is to chain together specialized components. In data-science this is the pipeline approach. Each component mostly treats the other components as I/O…
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The Deep Learning Roadmap – Intuition Machine – Medium

The Deep Learning Roadmap – Intuition Machine – Medium | EEDSP | Scoop.it
It just occurred to me, that after a couple of years tracking Deep Learning developments, that nobody has even bothered to create a map of what’s going on! So I quickly decided to come up with a Deep…
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Anything2Vec, or How Word2Vec Conquered NLP

Anything2Vec, or How Word2Vec Conquered NLP | EEDSP | Scoop.it
This is the website and blog of Yves Peirsman, Natural Language Processing Consultant.
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Introducing tf-seq2seq: An Open Source Sequence-to-Sequence Framework in TensorFlow

Introducing tf-seq2seq: An Open Source Sequence-to-Sequence Framework in TensorFlow | EEDSP | Scoop.it

An open source seq2seq framework in TensorFlow that makes it easy to experiment with seq2seq models and achieve state-of-the-art results. To that end, we made the tf-seq2seq codebase clean and modular, maintaining full test coverage and documenting all of its functionality.

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Open Datasets for Deep Learning - Deeplearning4j: Open-source, Distributed Deep Learning for the JVM

Open Datasets for Deep Learning - Deeplearning4j: Open-source, Distributed Deep Learning for the JVM | EEDSP | Scoop.it

Here you’ll find an organized list of interesting, high-quality datasets for machine learning research. We welcome your contributions for curating this list! You can find other lists of such datasets on Wikipedia, for example.

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A guide to receptive field arithmetic for Convolutional Neural Networks

A guide to receptive field arithmetic for Convolutional Neural Networks | EEDSP | Scoop.it
The receptive field is perhaps one of the most important concepts in Convolutional Neural Networks (CNNs) that deserves more attention from the literature. All of the state-of-the-art object…
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NVIDIA DGX-1: The Fastest Deep Learning System | Parallel Forall

NVIDIA DGX-1: The Fastest Deep Learning System | Parallel Forall | EEDSP | Scoop.it
NVIDIA DGX-1 is an integrated system for deep learning featuring eight Tesla P100 GPU accelerators connected through NVLink high-performance interconnect.
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How the Logistic Regression Model Works in Machine Learning | Open Data Science

How the Logistic Regression Model Works in Machine Learning | Open Data Science | EEDSP | Scoop.it
In this article, we are going to learn how the logistic regression model works in machine learning. The logistic regression model is one member of the
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Using MPI-3 Shared Memory in Intel® Xeon Phi™ Processors | Intel® Software

Using MPI-3 Shared Memory in Intel® Xeon Phi™ Processors | Intel® Software | EEDSP | Scoop.it
This whitepaper introduces the MPI-3 shared memory feature, the corresponding APIs, and a sample program to illustrate the use of MPI-3 shared memory in the Intel® Xeon Phi™ processor.
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Machine learning methods (infographic)

Machine learning methods (infographic) | EEDSP | Scoop.it
What’s the right algorithm for the task? Our visual primer shows the most common ones in use and the business problems they solve.
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Teaching Machines to Draw

Teaching Machines to Draw | EEDSP | Scoop.it
Posted by David Ha, Google Brain Resident Abstract visual communication is a key part of how people convey ideas to one another. From
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Caffe 2

NVIDIA and Facebook announced Caffe2. 

  

Cafe2: FA New Lightweight, Modular, and Scalable Deep Learning Framework

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Knowledge extraction from unstructured texts

Knowledge extraction from unstructured texts | EEDSP | Scoop.it
Foreword There is an unreasonable amount of information that can be extracted from what people publicly say on the internet. At Heuritech we use this information to better understand what people want, which products they like and why. This post explains from a scientific point of view what is Knowledge extraction and details a few…
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Recursive Neural Networks with PyTorch | Parallel Forall

Recursive Neural Networks with PyTorch | Parallel Forall | EEDSP | Scoop.it
PyTorch is a new deep learning framework that makes natural language processing and recursive neural networks easier to implement.
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Practicing Machine Learning with Optimism

Practicing Machine Learning with Optimism | EEDSP | Scoop.it
Using machine learning to solve real-world problems often presents challenges that weren't initially considered during the development of the machine learning method. This article addresses a few examples of such issues and hopefully provides some suggestions (and inspiration) for how to overcome the challenges using straightforward analyses on the data you already have.
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Google's dedicated TensorFlow processor, or TPU, crushes Intel, Nvidia in inference workloads - ExtremeTech

Google's dedicated TensorFlow processor, or TPU, crushes Intel, Nvidia in inference workloads - ExtremeTech | EEDSP | Scoop.it
Google has revealed new benchmark results for its custom TensorFlow processing unit, or TPU. In inference workloads, the company's ASI
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Federated Learning: Collaborative Machine Learning without Centralized Training Data

Federated Learning: Collaborative Machine Learning without Centralized Training Data | EEDSP | Scoop.it
Posted by Brendan McMahan and Daniel Ramage, Research Scientists Standard machine learning approaches require centralizing the trainin
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Fast memcpy Using SPDK and the Intel® I/OAT DMA Engine | Intel® Software

Fast memcpy Using SPDK and the Intel® I/OAT DMA Engine | Intel® Software | EEDSP | Scoop.it
Describes a usage of Intel® I/OAT DMA engine, with SPDK interfaced to the Intel® QuickData Technology Driver to move data in user space. The attached code sample compares memcpy and SKDK/Intel I/OAT performance when moving different size data chunks in memory.
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Go* for Big Data | Intel® Software

Go* for Big Data | Intel® Software | EEDSP | Scoop.it
Using Intel® Data Analytics Acceleration Library (Intel® DAAL) with the Go* programming language to enable batch, online, and distributed processing
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Natural Language Processing on 40 languages with the Ripple Down Rules-based Part-Of-Speech Tagger

Natural Language Processing on 40 languages with the Ripple Down Rules-based Part-Of-Speech Tagger | EEDSP | Scoop.it
Parts of Speech (POS) tagging is a crucial part in natural language processing. It consists of labelling each word in a text document with a certain category
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