A simple NLP library allows profiling datasets with one or more text columns. When given a dataset and a column name containing text data, NLP Profiler will return either high-level insights or low-level/granular statistical information about the text in that column.

Stars: ✭ 181 (-93.44%)

Mutual labels: jupyter-notebook, natural-language-processing

Notebooks

Jupyter Notebooks with Deep Learning Tutorials

Stars: ✭ 188 (-93.19%)

Mutual labels: jupyter-notebook, natural-language-processing

Keraspp

코딩셰프의 3분 딥러닝, 케라스맛

Stars: ✭ 178 (-93.55%)

Mutual labels: jupyter-notebook, rnn

Deep Learning With Python

Deep learning codes and projects using Python

Stars: ✭ 195 (-92.93%)

Mutual labels: jupyter-notebook, rnn

Graph Convolution Nlp

Graph Convolution Network for NLP

Stars: ✭ 208 (-92.46%)

Mutual labels: jupyter-notebook, natural-language-processing

Natural Language Processing With Tensorflow

Natural Language Processing with TensorFlow, published by Packt

Stars: ✭ 222 (-91.96%)

Mutual labels: jupyter-notebook, rnn

Text summarization with tensorflow

Implementation of a seq2seq model for summarization of textual data. Demonstrated on amazon reviews, github issues and news articles.

Stars: ✭ 226 (-91.81%)

Mutual labels: jupyter-notebook, natural-language-processing

Rnn For Joint Nlu

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

Stars: ✭ 176 (-93.62%)

Mutual labels: jupyter-notebook, rnn

View All Similar Projects ➔

DeepNLP-models-Pytorch

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning)

This is not for Pytorch beginners. If it is your first time to use Pytorch, I recommend these awesome tutorials.
If you're interested in DeepNLP, I strongly recommend you to work with this awesome lecture.
- cs-224n-slides
- cs-224n-videos

This material is not perfect but will help your study and research:) Please feel free to pull requests!!

Model	Links
01. Skip-gram-Naive-Softmax	[notebook / data / paper]
02. Skip-gram-Negative-Sampling	[notebook / data / paper]
03. GloVe	[notebook / data / paper]
04. Window-Classifier-for-NER	[notebook / data / paper]
05. Neural-Dependancy-Parser	[notebook / data / paper]
06. RNN-Language-Model	[notebook / data / paper]
07. Neural-Machine-Translation-with-Attention	[notebook / data / paper]
08. CNN-for-Text-Classification	[notebook / data / paper]
09. Recursive-NN-for-Sentiment-Classification	[notebook / data / paper]
10. Dynamic-Memory-Network-for-Question-Answering	[notebook / data / paper]

Requirements

Python 3.5
Pytorch 0.2+
nltk 3.2.2
gensim 2.2.0
sklearn_crfsuite

Getting started

git clone https://github.com/DSKSD/cs-224n-Pytorch.git

prepare dataset

cd script
chmod u+x prepare_dataset.sh
./prepare_dataset.sh

docker env

ubuntu 16.04 python 3.5.2 with various of ML/DL packages including tensorflow, sklearn, pytorch

docker pull dsksd/deepstudy:0.2

pip3 install docker-compose
cd script
docker-compose up -d

cloud setting

not yet

References

Author

Sungdong Kim / @DSKSD

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

DSKSD / Deepnlp Models Pytorch

Programming Languages

Labels

Projects that are alternatives of or similar to Deepnlp Models Pytorch

DeepNLP-models-Pytorch

Contents

Requirements

Getting started

prepare dataset

docker env

cloud setting

References

Author