Discover Kyeongpil/SelCa Open Source project

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2
Language
Python
Created about 4 years ago
Updated about 4 years ago

Kyeongpil

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PyTorch implementation of sequential recommender system (SelCa)

Dataset

Dataset I collected. Usually I have found these dataset in research papers.

crawler

some crawler codes that I made

Python

skt-exercise

skt 실습을 위한 자료입니다.

Jupyter Notebook

deep-joseon-record-analysis

Official implementation of restoration and translation of joseon historical records (NAACL 2021)

Python

naver-movie-rate-prediction

Jupyter Notebook

CandiVis

19대 대선 후보들을 시각화하여 분석하는 시스템입니다

JavaScript

opinion-leader-analysis

Analyze relationships between bitcoin prices and user group in online community

Jupyter Notebook

hierarchical-nmf-python

python codes for hierarchical rank2 nmf

MATLAB

khaiii-topicmodeling

Topic modeling using Kakao Hangul PoS analyzer

Jupyter Notebook

topicmodeling-exmaple

topicmodeling example using twitter data

Jupyter Notebook

bitcoin_topicmodeling

topic modeling & visualization exercise with bitcoin forum data

Jupyter Notebook

Paper-List

Movie-Rating-Prediction

Pytorch codes that I created for our lab study

Python

climate-topic-modeling

climate analysis using topic modeling

Jupyter Notebook

kakao-clone

kakao-clone study (html, css, javascript)

HTML

react-native-study

JavaScript

tools-for-research

some tools used in researches or papers

naver_simple_movie_recomm

example recommender system from crawling the naver movie

Jupyter Notebook

rudvlf0413.github.com

CSS

tomato-timer

JavaScript

Kyeongpil/SelCa

Kyeongpil

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