Yash Kumar Atri (yashkumaratri)

yashkumaratri

Geek Repo

Company:@IIITD @lcs2-iiitd @hartvigsen-group

Location:India

Home Page:yashkumaratri.github.io

Twitter:@yashkumaratri

Github PK Tool:Github PK Tool


Organizations
LCS2-IIITD

Yash Kumar Atri's repositories

conv-emotion

This repo contains implementation of different architectures for emotion recognition in conversations

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minimal-django-file-upload-example

Source code for example at http://stackoverflow.com/questions/5871730/need-a-minimal-django-file-upload-example

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StarGAN-Tensorflow

Simple Tensorflow implementation of StarGAN (CVPR 2018 Oral)

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pytorch-dual-learning

Implementation of Dual Learning NMT on PyTorch

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flappybird

A flappybird game in python2

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Pun-Finder

This model is trained over hundreds of PUNs and can do the 3 subtasks depicted in SEMEVAL 2017 Task 7

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awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

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ml-india

Website for Machine Learning India (ml-india). Fostering machine learning and data science ecosystem in India.

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Android-Mini-Projects

It contains android mini projects.

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GUI-Chat---FTP-server

A java project for GUI based chatserver and FTP based file transfer program

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Chat-App

A chat app programmed in Java

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Strunn-Speech-to-text

An upgraded version of Sphinx and Voce

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Computational-Knowledge-Engine

A stop destination for your queries and problems

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deeplearning4j

Deep Learning for Java, Scala & Clojure on Hadoop & Spark With GPUs - From Skymind

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awesome-public-datasets

An awesome list of high-quality open datasets in public domains (on-going). By everyone, for everyone!

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empath-client

analyze text with empath

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PGO_AIML

Default (ALICE clone) AIML set that is compatible with Program O

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lectures

Oxford Deep NLP 2017 course

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NLP-Extractive-NEWS-summarization-using-MMR

A simple python implementation of the Maximal Marginal Relevance (MMR) baseline system for text summarization.

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hacker-rank

This is a repository of my solutions to hacker rank problems.

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Text_Summarization-MMR_and_LexRank

Demonstration of automated summary construction with a) Maximal Marginal Relevance (MMR) as the baseline approach with an aim to reduce redundancy while maintaining query relevance in re-ranking retrieved documents and b) the introduction of sentence salience to identify most important sentences in documents with degree-based approach called LexRank to compute centrality using the similarity graphs.

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HW1

Template for CS287 HW1

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microsoft.github.io

The code behind the Microsoft.github.io website

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