\documentclass[a4paper]{article} | |
% XeTeX 관련 ================================================================= | |
% xltxtra Package가 fontspec을 부를 때 no-math 옵션을 주어 수식엔 영향을 주지 않게 함. | |
\PassOptionsToPackage{no-math}{fontspec} | |
\usepackage{xltxtra} | |
% Western과 CJK에 다른 글꼴을 사용하기 위한 패키지 | |
\usepackage{xeCJK} |
UPDATE: I have baked the ideas in this file inside a Python CLI tool called pyds-cli
. Please find it here: https://github.com/ericmjl/pyds-cli
Having done a number of data projects over the years, and having seen a number of them up on GitHub, I've come to see that there's a wide range in terms of how "readable" a project is. I'd like to share some practices that I have come to adopt in my projects, which I hope will bring some organization to your projects.
Disclaimer: I'm hoping nobody takes this to be "the definitive guide" to organizing a data project; rather, I hope you, the reader, find useful tips that you can adapt to your own projects.
Disclaimer 2: What I’m writing below is primarily geared towards Python language users. Some ideas may be transferable to other languages; others may not be so. Please feel free to remix whatever you see here!
import React from 'react'; | |
import PropTypes from 'prop-types'; | |
import SyntaxHighlighter from 'react-syntax-highlighter'; | |
export default class CodeBlock extends React.PureComponent { | |
static propTypes = { | |
value: PropTypes.string.isRequired, | |
language: PropTypes.string, | |
} |
약자 | 한국정보과학회 (2024) | BK21플러스 IF (2018) | KAIST CS (2022) | SNU CSE (2024.4) | POSTECH CSE (2024.9) | 평균 (정규화) | 학회명 | DBLP Key | |
---|---|---|---|---|---|---|---|---|---|
AAAI | 최우수 | 4 | O | O | 최우수 | 1.00 | AAAI Conference on Artificial Intelligence (AAAI) | conf/aaai | |
AAMAS | 우수 | 2 | 0.20 | International Conference on Autonomous Agents and Multiagent Systems (AAMAS) | conf/ifaamas | ||||
ACCV | 우수 | 1 | 우수 | 0.25 | Asian Conference on Computer Vision (ACCV) | conf/accv | |||
ACL | 최우수 | 4 | O | O | 최우수 | 1.00 | Annual Meeting of the Association for Computational Linguistics (ACL) | conf/acl | |
ACL Findings | 우수 | 우수 | 0.20 | Findings of ACL | series/findacl | ||||
ACNS | 우수 | 0.10 | International Conference on Applied Cryptography and Network Security (ACNS) | conf/acns | |||||
ACSAC | 우수 | 2 | 우수 | 0.30 | Annual Computer Security Applications Conference (ACSAC) | conf/acsac | |||
AIED | 우수 | 0.10 | International Conference on Artificial Intelligence in Education (AIED) | conf/aied | |||||
AISTATS | 우수 | 1 | 우수 | 0.25 | International Conference on Artificial Intelligence and Statistics (AISTATS) | conf/aistats |