SUNIL KUMAR SAHU (sunilitggu)

sunilitggu

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Location:Abu Dhabi

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SUNIL KUMAR SAHU's repositories

relation_extraction_in_clinical_text

CNN for relation extraction among problem, treatment and test in clinical text.

DDI-extraction-through-LSTM

DDI Extraction from Biomedical text using LSTM network

tensorflow_ner

tensorflow implementation of CNN+BLSTM+CRF model for entity recognition

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Coursera-Machie-Learning-

All programming assignment of Andrew's machine learning course

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sunilitggu.github.io

Sunil's Personal Website

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Annotated-Semantic-Relationships-Datasets

Public and free annotated datasets of relationships between entities/nominals

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CNN-RelationExtraction

Convolution neural network for relation extraction between two given entities

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coding_practice

Practice for coding interviews

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cs224d-solutions

Solutions for http://cs224d.stanford.edu/

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fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

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HFT-CNN

Convolutional Neural Network based on Hierarchical Category Structure for Multi-label Short Text Categorization

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Natural_Language_Processing

NLP courseworks (Python)

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nlp-datasets

A list of datasets/corpora for NLP tasks, in reverse chronological order.

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nn-from-scratch

Implementing a Neural Network from Scratch

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nn-theano

Speed up your Neural Network with Theano and the GPU

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OpenNMT-py

Open Source Neural Machine Translation in PyTorch

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phenochf-corpus

Automatically exported from code.google.com/p/phenochf-corpus

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practNLPTools

Practical Natural Language Processing Tools for Humans. Dependency Parsing, Syntactic Constituent Parsing, Semantic Role Labeling, Named Entity Recognisation, Shallow chunking, Part of Speech Tagging, all in Python.

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RecursiveNN

Tensorflow implementation of Recursive Neural Networks using LSTM units

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rnn-tutorial-rnnlm

Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano

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seq2seq

A general-purpose encoder-decoder framework for Tensorflow

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TEES

Turku Event Extraction System

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tensorflow-tutorial

tutorial for tensorflow

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