krayush07
Machine Learning Scientist, Worked on Episodic Memory, Worked on Sentiment Analysis
IIT PatnaBangalore, India
Pinned Repositories
awesome-deep-learning-papers
The most cited deep learning papers
cnn-text-classification
deep-attention-text-classifier-tf
Deep-Attention Text Classifier in Tensorflow
learn-by-weak-supervision
A meta-learning setup to utitlize the unlabeled data for target task. An implementation of "Learning to learn from weak supervision by full supervision". https://arxiv.org/abs/1711.11383
SemEval
SemEval ABSA 2016
sequential-match-network
A deep learning framework to selection next response for current input utterance conditioned on previous contexts.
TopDeepLearning
A list of popular github projects related to deep learning
unsupervised-aspect-extraction
An unsupervised method to extract aspects from customer reviews.
utility-codes
Repository for common and utility codes.
krayush07's Repositories
krayush07/deep-attention-text-classifier-tf
Deep-Attention Text Classifier in Tensorflow
krayush07/learn-by-weak-supervision
A meta-learning setup to utitlize the unlabeled data for target task. An implementation of "Learning to learn from weak supervision by full supervision". https://arxiv.org/abs/1711.11383
krayush07/sequential-match-network
A deep learning framework to selection next response for current input utterance conditioned on previous contexts.
krayush07/cnn-text-classification
krayush07/unsupervised-aspect-extraction
An unsupervised method to extract aspects from customer reviews.
krayush07/utility-codes
Repository for common and utility codes.
krayush07/awesome-deep-learning-papers
The most cited deep learning papers
krayush07/SemEval
SemEval ABSA 2016
krayush07/TopDeepLearning
A list of popular github projects related to deep learning
krayush07/autoencoder
Autoencoder and visualization for MNIST
krayush07/awesome-mlops
A curated list of references for MLOps
krayush07/awesome-rnn
Recurrent Neural Network - A curated list of resources dedicated to RNN
krayush07/caml-mimic
multilabel classification of EHR notes
krayush07/ConvNet
Convolutional Neural Networks for Matlab, including Invariang Backpropagation algorithm (IBP). Has versions for GPU and CPU, written on CUDA, C++ and Matlab. All versions work identically. The GPU version uses kernels from Alex Krizhevsky's library 'cuda-convnet2'.
krayush07/CS-7641-Machine-Learning-Notes
In this repository, I will publish my notes for GaTech's Machine Learning course CS7641.
krayush07/deeplearnjs
Hardware-accelerated deep learning and linear algebra (NumPy) library for the web.
krayush07/krayush07.aboutme.com
krayush07/krayush07.github.io
krayush07/linear-regression
Linear Regression in Python
krayush07/machine-learning-cheat-sheet
Classical equations and diagrams in machine learning
krayush07/Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
krayush07/nlp-phd-global-equality
A repo for open resources & information for people to succeed in PhD in CS & career in AI / NLP
krayush07/optimus
Train, evaluate and deploy Deep Learning based text classifiers. Currently supports CNN
krayush07/reddit-top-2.5-million
This is a dataset of the all-time top 1,000 posts, from the top 2,500 subreddits by subscribers, pulled from reddit between August 15–20, 2013.
krayush07/scikit-learn
scikit-learn: machine learning in Python
krayush07/TensorFlow-Examples
TensorFlow tutorials and code examples for beginners
krayush07/tensorflow-worklab
This set of files is an example of how to use Tensorflow for importing and retraining an existing model, such as ResNet. The goal of this example is to separate all functionality on several classes, so it is easy to modify the parameters and run the models, while still having all code not too deep inside.
krayush07/tf-idf
Python package to extract significant keywords.
krayush07/tf-vgg
This repository contains script for VGG model in tensorflow.
krayush07/Theano
Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.