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deeplearning4j-docs - Documentation for Deeplearning4j - Deep Learning for the JVM, Java & Scala

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The documentation for Deeplearning4j and all of its libraries (DL4J, ND4J, Arbiter, DataVec, etc.) live in this repository. Warning: DO NOT edit the user guide directly in this repository. Commits will be reverted. Please make changes to the main repository here, run the autogeneration process, and open a pull request.

TSNE-Embedding-Visualisation - A Simple and easy to use way to Visualise Embeddings!

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A Simple and easy to use way to Visualise Embeddings! Blog post on this project is here. This project is forked from Tensorflow's Standalone Embedding Projector. It shows how a pretrained InceptionV3 model can be used on images and plotted in an interactive 3d map.

Deep-Survey-Text-Classification - The project surveys 16+ Natural Language Processing (NLP) research papers that propose novel Deep Neural Network Models for Text Classification, based on Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN)

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This is a survey on deep learning models for text classification and will be updated frequently with testing and evaluation on different datasets. Natural Language Processing tasks ( part-of-speech tagging, chunking, named entity recognition, text classification, etc .) has gone through tremendous amount of research over decades. Text Classification has been the most competed NLP task in kaggle and other similar competitions. Count based models are being phased out with new deep learning models emerging almost every month. This project is an attempt to survey most of the neural based models for text classification task. Models selected, based on CNN and RNN, are explained with code (keras and tensorflow) and block diagrams. The models are evaluated on one of the kaggle competition medical dataset.