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2021-06-25 읽을거리읽을거리 2021. 6. 25. 22:13
python
1. python에서 사용하는 메모리 확인하는 방법 및 코드
https://pythonspeed.com/articles/measuring-memory-python/
Measuring memory usage in Python: it’s tricky!
If you want your program to use less memory, you will need to measure memory usage. You’ll want to measure the current usage, and then you’ll need to ensure it’s using less memory once you make some improvements. It turns out, however, that measuring
pythonspeed.com
2. HTTP 통신에 사용하는 라이브러리 6가지
https://www.scrapingbee.com/blog/best-python-http-clients/
The best Python HTTP clients for 2021
This article will discuss the best HTTP clients in Python. Requests, AIOHTTP, GRequests...it can be hard to choose the best one.
www.scrapingbee.com
3. auto_all : 전역 변수, 함수로 자동적으로 선언해주는 라이브러리
https://github.com/jongracecox/auto-all
jongracecox/auto-all
Automatically manage the __all__ variable in Python modules. - jongracecox/auto-all
github.com
4. python으로 작성한 미니 프로젝트들 소개
https://levelup.gitconnected.com/21-python-mini-projects-with-codes-c4126e4131e4
21 Python Mini Projects With Code
The Best way to learn a programming language is to build projects in it
levelup.gitconnected.com
5. python function에 대한 5가지 개념 및 예제 코드
5 Advanced Python Function Concepts Explained With Examples
Lambdas, decorators, partials, and more
betterprogramming.pub
6. python의 built-in module 11가지에 대한 설명 및 예제
11 Most Useful Built-in Python Modules You Might Not Know Yet
You don’t have to write codes from scratch.
levelup.gitconnected.com
Data Science
1. Transformer 튜토리얼
Huffon/klue-transformers-tutorial
KLUE 데이터를 활용한 HuggingFace Transformers 튜토리얼. Contribute to Huffon/klue-transformers-tutorial development by creating an account on GitHub.
github.com
2. pandas에 대한 좀 더 심도 깊은 사용법
https://towardsdatascience.com/20-great-pandas-tricks-for-data-science-3a6daed71da0
20 Great Pandas Tricks For Data Science
20 Great Pandas tricks that you should use every day.
towardsdatascience.com
3. GPU 기반으로 머신러닝 모델을 사용하는 RAPIDS CuML 과 scikit-learn를 앙상블하여 더욱 빠르게 모델링하는 법
100x Faster Machine Learning Model Ensembling with RAPIDS cuML and Scikit-Learn Meta-Estimators
Learn how to use RAPIDS cuML with scikit-learn’s ensemble model APIs to achieve more than 100x faster boosting, bagging, and stacking.
medium.com
4. scaling 과 normalizing에 대한 각각의 방법론들의 예제를 작성해놓음
100x Faster Machine Learning Model Ensembling with RAPIDS cuML and Scikit-Learn Meta-Estimators
Learn how to use RAPIDS cuML with scikit-learn’s ensemble model APIs to achieve more than 100x faster boosting, bagging, and stacking.
medium.com
5. pandas에서 통계 분석에 일반적으로 사용되는 함수들에 대한 설명
https://medium.com/analytics-vidhya/statistical-analysis-in-python-using-pandas-27c6a4209de2
Statistical Analysis in Python using Pandas
In the next few minutes, we shall get ‘Pandas’ covered — An extremely popular Python library that comes with high-level data structures…
medium.com
6. Naver AI Lab에서 논문을 낸 Re-labeling 방법론에 대한 소개
https://github.com/naver-ai/relabel_imagenet
naver-ai/relabel_imagenet
Contribute to naver-ai/relabel_imagenet development by creating an account on GitHub.
github.com
UI / UX
1. palanteer : 메모리 사용량, 에러 발생, 함수 시간 등 개발에 진행됨에 필요한 정보들을 종합적으로 시각화하는 솔루션 라이브러리
https://github.com/dfeneyrou/palanteer
dfeneyrou/palanteer
High performance visual profiler, debugger, tests enabler for C++ and Python - dfeneyrou/palanteer
github.com
2. sierra : html와 css를 python 코드 상에서 사용하여 웹 페이지를 제작하는 라이브러리
https://github.com/BrainStormYourWayIn/sierra
BrainStormYourWayIn/sierra
Sierra is a lightweight Python framework for building and integrating web applications - BrainStormYourWayIn/sierra
github.com
3. 데이터 탐색을 GUI로 보여주는 웹사이트
https://medium.com/people-ai-research/know-your-data-a-new-tool-to-explore-datasets-ba45b7665695
Know Your Data: a new tool to explore datasets
Designed to help researchers and product teams better understand datasets, improve data quality and mitigate bias issues.
medium.com
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