jisu1013's Stars
kakaobank/KF-DeBERTa
카카오뱅크 & 에프엔가이드에서 학습한 금융 도메인 특화 언어모델
kairess/paper2video
Summarize research papers and pdf books into YouTube shorts videos. 100% 자동 논문/소설 요약/번역 및 1분 요약 유튜브 영상 제작 인공지능
Beomi/KoAlpaca
KoAlpaca: 한국어 명령어를 이해하는 오픈소스 언어모델
acheong08/ChatGPT
Reverse engineered ChatGPT API
openai/openai-cookbook
Examples and guides for using the OpenAI API
BM-K/KoSimCSE-SKT
Simple Contrastive Learning of Korean Sentence Embeddings
VSFe/Tech-Interview
PacktPublishing/Python-Feature-Engineering-Cookbook
Python Feature Engineering Cookbook, published by Packt
rickiepark/nlp-with-transformers
<트랜스포머를 활용한 자연어 처리> 예제 코드를 위한 저장소입니다.
youssefHosni/Data-Science-Interview-Questions-Answers
Curated list of data science interview questions and answers
galhev/Neural-Sentiment-Analyzer-for-Modern-Hebrew
Neural Sentiment Analyzer for Modern Hebrew
ukairia777/tensorflow-nlp-tutorial
tensorflow를 사용하여 텍스트 전처리부터, Topic Models, BERT, GPT, LLM과 같은 최신 모델의 다운스트림 태스크들을 정리한 Deep Learning NLP 저장소입니다.
zenwan/Wide-and-Deep-PyTorch
PyTorch implementation of Tensorflow's Wide and Deep Algorithm
Park-Ju-hyeong/Wide-Deep-Learning
lsjsj92/recommender_system_with_Python
recommender system tutorial with Python
CausalInferenceLab/Causal-Inference-with-Python
Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.
supkoon/wide_deep
jrzaurin/Wide-and-Deep-Keras
Keras implementation of Tensorflow's Wide and Deep Algorithm
LeeHyeJin91/Wide_and_Deep
wide and deep tensorflow 2.0
shenweichen/DeepCTR-Torch
【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.
sisinflab/adversarial-recommender-systems-survey
The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-dimensional) data distributions. In this survey, we provide an exhaustive literature review of 74 articles published in major RS and ML journals and conferences. This review serves as a reference for the RS community, working on the security of RS or on generative models using GANs to improve their quality.
SeongJinAhn/VGNAE
(CIKM'21) Variational Graph Normalized Auto-Encoders
cmavro/Graph-InfoClust-GIC
[PAKDD 2021] Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
gyusu/Kiwoom_datareader
키움증권 Open API를 사용하여 주가 데이터를 받아오는 PyQt 기반의 프로그램
gordicaleksa/get-started-with-JAX
The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.
Coder-Yu/QRec
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
cowjen01/repsys
Framework for Interactive Evaluation of Recommender Systems
ceo21ckim/DGL-Tutorial
This Repository includes DGL tutorials and various information related to graph neural networks.
UpstageAI/2022-lguplus-AI-Ground
jihoo-kim/Awesome-Generative-RecSys
A curated list of Generative Recommender Systems (Paper & Code)