ktasha45's Stars
nomic-ai/gpt4all
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
EthicalML/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
lukas-blecher/LaTeX-OCR
pix2tex: Using a ViT to convert images of equations into LaTeX code.
dair-ai/ML-Papers-of-the-Week
🔥Highlighting the top ML papers every week.
brave-people/Dev-Event
🎉🎈 개발자 {웨비나, 컨퍼런스, 해커톤} 행사를 알려드립니다. [with 남송리 삼번지]
wiseodd/generative-models
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Atcold/NYU-DLSP20
NYU Deep Learning Spring 2020
zhangqianhui/AdversarialNetsPapers
Awesome paper list with code about generative adversarial nets
ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
mukulpatnaik/researchgpt
A LLM based research assistant that allows you to have a conversation with a research paper
teddylee777/machine-learning
머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)
guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.
probml/pml2-book
Probabilistic Machine Learning: Advanced Topics
asheeshcric/awesome-contrastive-self-supervised-learning
A comprehensive list of awesome contrastive self-supervised learning papers.
python-adaptive/adaptive
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
Vincentqyw/cv-arxiv-daily
🎓Automatically Update CV Papers Daily using Github Actions
Lionelsy/Conference-Accepted-Paper-List
Some Conferences' accepted paper lists (including AI, ML, Robotic)
PacktPublishing/Hands-On-Graph-Neural-Networks-Using-Python
Hands-On Graph Neural Networks Using Python, published by Packt
jihoo-kim/Awesome-Generative-RecSys
A curated list of Generative Recommender Systems (Paper & Code)
sjhwang82/AdvancedML
Reading list for the Advanced Machine Learning Course
kakao/recoteam
카카오 추천팀 공개 리포지토리입니다.
reinforcement-learning-kr/how_to_study_rl
The text for those who want to study reinforcement learning in Korean
Alro10/awesome-deep-neuroevolution
A collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)
junhsss/consistency-models
A Toolkit for OpenAI's Consistency Models.
ceo21ckim/Awesome-Recsys
This Repository includes recent papers (RecSys, SIGIR, WWW, etc.) related to the Recommender Systems
ddobokki/chatgpt_stock_report
그날의 증권사 리포트를 챗 gpt를 활용해 요약하는 레포
SeongBeomLEE/RecSys-Tech-Blog-Article
추천 시스템 관련 자료 모음
stevenliuyi/information-bottleneck
demonstration of the information bottleneck theory for deep learning
l-yohai/daily_papers_ko
This project aims to automatically translate and summarize Huggingface's daily papers into Korean using ChatGPT.
YuzheSHI/generative-modeling-explained
Ying Nian Wu's UCLA Statistical Machine Learning Tutorial on generative modeling.