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๊ฐœ๋ฐœ Code 50

[Python][AI] AutoGluon: ์‰ฝ๊ณ  ๋น ๋ฅธ ๋จธ์‹ ๋Ÿฌ๋‹ ์ž๋™ํ™” ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ

1. AutoGluon ๊ฐœ์š” ๋ฐ ์—ฐํ˜AutoGluon์€ AWS(Amazon Web Services)์—์„œ ๊ฐœ๋ฐœํ•œ AutoML(Automated Machine Learning) ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ๋กœ, ๋จธ์‹ ๋Ÿฌ๋‹ ๋ชจ๋ธ์„ ์‰ฝ๊ณ  ๋น ๋ฅด๊ฒŒ ํ•™์Šตํ•  ์ˆ˜ ์žˆ๋„๋ก ์ง€์›ํ•œ๋‹ค. 2019๋…„ ์ฒ˜์Œ ๊ณต๊ฐœ๋˜์—ˆ์œผ๋ฉฐ, ์ตœ์‹  SOTA(State-of-the-Art) ๋ชจ๋ธ์„ ์ž๋™์œผ๋กœ ํ™œ์šฉํ•˜์—ฌ ๋†’์€ ์„ฑ๋Šฅ์„ ์ œ๊ณตํ•˜๋Š” ๊ฒƒ์ด ํŠน์ง•์ด๋‹ค. ์ฃผ์š” ํŠน์ง•:3์ค„์˜ ์ฝ”๋“œ๋กœ ๋จธ์‹ ๋Ÿฌ๋‹ ๋ชจ๋ธ ๊ตฌ์ถ• ๊ฐ€๋Šฅ์ตœ์‹  ๋”ฅ๋Ÿฌ๋‹ ๋ฐ ๋จธ์‹ ๋Ÿฌ๋‹ ๊ธฐ๋ฒ• ์ž๋™ ์ ์šฉ๊ฐ„ํŽธํ•œ ๋ฐฐํฌ ๋ฐ ํ™•์žฅ์„ฑ ์ œ๊ณต๋‹ค์–‘ํ•œ ๋ฐ์ดํ„ฐ ์œ ํ˜• ์ง€์›(ํ‘œํ˜• ๋ฐ์ดํ„ฐ, ์ด๋ฏธ์ง€, ํ…์ŠคํŠธ, ์‹œ๊ณ„์—ด ๋“ฑ)2. AutoGluon์˜ ์ฃผ์š” ๊ธฐ๋ŠฅAutoGluon์€ ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ํ•™์Šต ์œ ํ˜•์„ ์ง€์›ํ•˜๋ฉฐ, ๋ฐ์ดํ„ฐ ์œ ํ˜•์— ๋”ฐ๋ผ ์ตœ์ ์˜ ๋ชจ๋ธ์„ ์ž๋™์œผ๋กœ ์„ ํƒํ•˜์—ฌ ํ•™์Šตํ• ..

[Supplement][Docker] Building and Managing Docker Images

A Docker image is a read-only template that contains everything needed to run a container, including the application, libraries, and configuration files. This guide outlines efficient methods for building and managing Docker images.1. Building a Docker Image1.1 Writing a DockerfileA Docker image is created based on a Dockerfile.Here is a basic example:# Set base imageFROM python:3.9# Set working..

[Supplement][Docker] Understanding Docker

๐Ÿณ What is Docker?Docker is a container-based virtualization technology that allows applications and their dependencies to be packaged into containers, enabling them to run consistently across different environments.Unlike virtual machines (VMs), which virtualize an entire operating system, Docker shares the host OS kernel while providing isolated environments for applications.Key Concepts of Do..

[Python][program] CLI ASCII art ๋ฐœ๋ Œํƒ€์ธ ๋ฉ”์„ธ์ง€ ์“ฐ๊ธฐ

Python์„ ํ™œ์šฉํ•ด ๋ฐœ๋ Œํƒ€์ธ ๋ฐ์ด์— ์ง์ ‘ ๋งŒ๋“  ASCII ์•„ํŠธ ์นด๋“œ๋ฅผ ํ„ฐ๋ฏธ๋„์—์„œ ์ถœ๋ ฅํ•ด๋ณด๋ฉด ์–ด๋–จ๊นŒ? ๋ผ๋Š” ์ƒ๊ฐ์œผ๋กœ ์ž‘์—…์„ ์ง„ํ–‰ํ–ˆ๋‹ค. cowsay๊ฐ€ ๋– ์˜ฌ๋ž๊ณ  ์ด๊ฑธ ํ™œ์šฉํ•ด์„œ ๋งŒ๋“ค์–ด๋ณด๋ฉด ์žฌ๋ฐŒ๊ฒ ๋‹ค ์‹ถ์—ˆ๋‹ค.ํ•˜ํŠธ๋‚˜ ์นด๋“œ ๋ชจ์–‘์„ ์ถœ๋ ฅํ•˜๊ณ , ์›ํ•˜๋Š” ๋ฌธ๊ตฌ๋ฅผ ์ž…๋ ฅ๋ฐ›์•„ ํŠน๋ณ„ํ•œ ๋ฉ”์‹œ์ง€๋ฅผ ๋‚จ๊ธธ ์ˆ˜ ์žˆ๊ฒŒ๋” ์ž‘์—…ํ–ˆ๋‹ค. ์ฃผ์š” ํฌ์ธํŠธ:Python์—์„œ ํ…์ŠคํŠธ๋ฅผ ์ž๋™ ์ค„๋ฐ”๊ฟˆํ•ด์ฃผ๋Š” textwrap ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ ์‚ฌ์šฉASCII ์•„ํŠธ๋ฅผ ๋ฌธ์ž์—ด๋กœ ๊ตฌ์„ฑ์‚ฌ์šฉ์ž ์ž…๋ ฅ์„ ๋ฐ›์•„์„œ ์นด๋“œ ๋‚ด์šฉ์— ๋ฐ˜์˜ํ•˜์ง€๋งŒ ํ•œ๊ธ€๋กœ ์ง„ํ–‰ํ•˜๋ ค๋‹ˆ ์ž๋ฆฌ๊ฐ€ ์ž˜ ๋งž์ง€ ์•Š๋Š” ๋ฌธ์ œ๋Š” ๋‚จ๊ฒจ๋‘์—ˆ๋‹ค. ์˜์–ด๋กœ ์ž‘์„ฑํ•ด ๋ณด์‹œ๋ผ. import textwrapdef generate_valentine_card(message): # ๋ฉ”์‹œ์ง€๋ฅผ ์ค„๋ฐ”๊ฟˆํ•˜์—ฌ ์ •๋ฆฌ (์ตœ๋Œ€ 15์ž ๊ธฐ์ค€ ์ค„๋ฐ”๊ฟˆ) wrappe..

[WebDev][App] ๋ฐœ๋ Œํƒ€์ธ ๊ธฐ๋… ๋ฐœ๋ Œํƒ€์ธ ์นด๋“œ ์›น์•ฑ ๊ตฌํ˜„

๋ฐœ๋ Œํƒ€์ธ ๋ฐ์ด๋•Œ ํ• ๋งŒํ•œ ๋„ˆ๋“œ๊ฐ™์€ ํ–‰๋™ ์ค‘ ํ• ๋งŒํ•œ๊ฒŒ ๋ญ๊ฐ€ ์žˆ์„๊นŒ ๊ณ ๋ฏผํ•˜๋‹ค๊ฐ€ HTML + CSS๋ฅผ ํ™œ์šฉํ•œ ๋ฐœ๋ Œํƒ€์ธ ์นด๋“œ ๋งŒ๋“ค๊ธฐ๋ฅผ ํ•˜๋ฉด ์ข‹๊ฒ ๋‹ค ์‹ถ์–ด์„œ  GPT์™€ ํˆฌ๋‹ฅํˆฌ๋‹ฅ ๋งŒ๋“ค์–ด ๋ณด์•˜๋‹ค. ์ฝ”๋“œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. โค๏ธ Happy Valentine's Day! Send  ๊ธฐ๋ณธ ๋ธŒ๋ผ์šฐ์ €๋กœ ์—ด๋ฉด ๋™์ž‘ํ•  ๊ฒƒ์ด๋‹ค. ์ด์ œ ์˜ˆ์˜๊ฒŒ ๊พธ๋ฏธ๋Š” ๊ฒƒ์€ ๋‹น์‹ ์˜ ๋ชซ.

[WebDev][Node.js] Setting Up a Node.js Environment and Building a Server with Express.js

1. Setting Up Node.js in VSCode1.1. Installing Node.jsDownload and install the LTS version of Node.js from the official Node.js website.After installation, open a terminal and verify that Node.js and npm are installed correctly:node -v # Check Node.js versionnpm -v # Check npm version  * For Linux users, you can install Node.js and npm using the following command:sudo apt-get install nodejs n..

[WebDev][Node.js] What is Node.js? Understanding the Basics and Key Features

1. What is Node.js?Node.js is an open-source, cross-platform JavaScript runtime environment built on the Chrome V8 JavaScript engine. Traditionally, JavaScript was only executed in web browsers, but with Node.js, JavaScript can now run on servers as well.2. Key Features of Node.js2.1. Single-Threaded Event LoopNode.js operates on a single-threaded model but uses an event loop and asynchronous I/..

[Python][pandas] Loading Data - CSV

What is a CSV File?One of the most commonly used formats in data analysis is CSV (Comma-Separated Values). CSV files store data in a simple text format, where values are separated by commas (or other delimiters).Pandas provides a powerful function, read_csv(), to easily load CSV files into a DataFrame. In this guide, we will explore what a CSV file is, how to load it using Pandas, key parameters..

[Python][pandas] Exploring pandas in Depth

What is Pandas?  Pandas is an open-source Python library designed for data manipulation and analysis. It was developed by Wes McKinney in 2008 when he saw the need for an efficient and intuitive tool to handle financial data. The name "Pandas" originates from "PANel DAta," reflecting its focus on handling multidimensional data structures.   Built on top of NumPy, Pandas provides a powerful and f..

[Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 4

2025.02.10 - [๊ฐœ๋ฐœ Code/์ธ๊ณต์ง€๋Šฅ A.I.] - [Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 12025.02.10 - [๊ฐœ๋ฐœ Code/์ธ๊ณต์ง€๋Šฅ A.I.] - [Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 22025.02.10 - [๊ฐœ๋ฐœ Code/์ธ๊ณต์ง€๋Šฅ A.I.] - [Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 3 1. IntroductionIn this section, we will use the XGBoost regression model to pre..

[Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 3

2025.02.10 - [๊ฐœ๋ฐœ Code/์ธ๊ณต์ง€๋Šฅ A.I.] - [Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 12025.02.10 - [๊ฐœ๋ฐœ Code/์ธ๊ณต์ง€๋Šฅ A.I.] - [Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 2 In this section, we will visualize the relationships between variables and identify key patterns in the dataset.Wine Quality Distribution & Correlation Analysis# Library Version# pandas..

[Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 2

2025.02.10 - [๊ฐœ๋ฐœ Code/์ธ๊ณต์ง€๋Šฅ A.I.] - [Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 1 [Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 1Exploratory Data Analysis (EDA) is the first step in data analysis, where data is visually explored, summary statistics are examined, and patterns and characteristics of the dataset are identified. In this post, we will ..

[Python][AI] Exploratory Data Analysis (EDA) - Wine Quality Dataset - 1

Exploratory Data Analysis (EDA) is the first step in data analysis, where data is visually explored, summary statistics are examined, and patterns and characteristics of the dataset are identified. In this post, we will walk through the step-by-step process of exploring data using the Wine Quality Dataset.What is EDA?EDA (Exploratory Data Analysis) is a crucial process for gaining a deeper under..

[Python][numpy] Numpy๋กœ ํšจ์œจ์ ์ธ ๋ฐ์ดํ„ฐ ์ƒ˜ํ”Œ๋ง ๋ฐ ๋‚œ์ˆ˜ ์ƒ์„ฑ

๋ฐ์ดํ„ฐ ๋ถ„์„ ๋ฐ ๋จธ์‹ ๋Ÿฌ๋‹์—์„œ๋Š” ๋‚œ์ˆ˜(random number) ์ƒ์„ฑ๊ณผ ์ƒ˜ํ”Œ๋ง(sampling)์ด ์ž์ฃผ ์‚ฌ์šฉ๋œ๋‹ค. Numpy์˜ np.random ๋ชจ๋“ˆ์„ ํ™œ์šฉํ•˜๋ฉด ๋‹ค์–‘ํ•œ ํ™•๋ฅ  ๋ถ„ํฌ์—์„œ ๋‚œ์ˆ˜๋ฅผ ์ƒ์„ฑํ•˜๊ณ  ๋ฐ์ดํ„ฐ๋ฅผ ์ƒ˜ํ”Œ๋งํ•  ์ˆ˜ ์žˆ๋‹ค.1. ๋‚œ์ˆ˜ ์ƒ์„ฑ์˜ ๊ธฐ๋ณธ1.1 ๊ท ๋“ฑ ๋ถ„ํฌ ๋‚œ์ˆ˜ ์ƒ์„ฑ๊ท ๋“ฑ ๋ถ„ํฌ์—์„œ ๋‚œ์ˆ˜๋ฅผ ์ƒ์„ฑํ•˜๋ ค๋ฉด np.random.rand() ๋˜๋Š” np.random.uniform()์„ ์‚ฌ์šฉํ•˜๋ฉด ๋จimport numpy as np# 0๊ณผ 1 ์‚ฌ์ด์˜ ๋‚œ์ˆ˜ 5๊ฐœ ์ƒ์„ฑrandom_numbers = np.random.rand(5)print(random_numbers)# [0.68210576 0.42857438 0.15101299 0.54555321 0.02568058]# ํŠน์ • ๋ฒ”์œ„(์˜ˆ: 10~20)์—์„œ ๊ท ๋“ฑ ๋ถ„ํฌ ๋‚œ์ˆ˜ 5๊ฐœ..

[Supplement][Docker] ๋„์ปค ์ด๋ฏธ์ง€ ๋นŒ๋“œ ๋ฐ ๊ด€๋ฆฌ

๋„์ปค ์ด๋ฏธ์ง€๋Š” ์ปจํ…Œ์ด๋„ˆ ์‹คํ–‰์— ํ•„์š”ํ•œ ๋ชจ๋“  ์š”์†Œ(์• ํ”Œ๋ฆฌ์ผ€์ด์…˜, ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ, ํ™˜๊ฒฝ ์„ค์ • ๋“ฑ)๋ฅผ ํฌํ•จํ•˜๋Š” ์ฝ๊ธฐ ์ „์šฉ ํ…œํ”Œ๋ฆฟ์ด๋‹ค. ์ด๋ฅผ ํšจ์œจ์ ์œผ๋กœ ๋นŒ๋“œํ•˜๊ณ  ๊ด€๋ฆฌํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ •๋ฆฌํ•œ๋‹ค.1. ๋„์ปค ์ด๋ฏธ์ง€ ๋นŒ๋“œ1.1 ๋„์ปคํŒŒ์ผ(Dockerfile) ์ž‘์„ฑ๋„์ปค ์ด๋ฏธ์ง€๋Š” Dockerfile์„ ๊ธฐ๋ฐ˜์œผ๋กœ ์ƒ์„ฑ๋จ ๊ธฐ๋ณธ์ ์ธ Dockerfile ์˜ˆ์‹œ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์Œ:# ๋ฒ ์ด์Šค ์ด๋ฏธ์ง€ ์„ค์ •FROM python:3.9# ์ž‘์—… ๋””๋ ‰ํ„ฐ๋ฆฌ ์„ค์ •WORKDIR /app# ํ•„์š” ํŒจํ‚ค์ง€ ๋ณต์‚ฌ ๋ฐ ์„ค์น˜COPY requirements.txt .RUN pip install -r requirements.txt# ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ๋ณต์‚ฌCOPY . .# ์‹คํ–‰ ๋ช…๋ น์–ด ์„ค์ •CMD ["python", "app.py"]1.2 ๋„์ปค ์ด๋ฏธ์ง€ ๋นŒ๋“œ์œ„ Dockerfile์„ ๊ธฐ๋ฐ˜์œผ..

[Python][numpy] Numpy ๋ฐฐ์—ด ์ €์žฅ ๋ฐ ๋ถˆ๋Ÿฌ์˜ค๊ธฐ

Numpy๋Š” ๋ฐ์ดํ„ฐ๋ฅผ ์ €์žฅํ•˜๊ณ  ๋‹ค์‹œ ๋ถˆ๋Ÿฌ์˜ค๋Š” ๋‹ค์–‘ํ•œ ๋ฐฉ๋ฒ•์„ ์ œ๊ณตํ•œ๋‹ค. ์ด ๊ธ€์—์„œ๋Š” Numpy ๋ฐฐ์—ด์„ ํŒŒ์ผ๋กœ ์ €์žฅํ•˜๊ณ , ๋‹ค์‹œ ๋ถˆ๋Ÿฌ์˜ค๋Š” ๋ฐฉ๋ฒ•์„ ์ •๋ฆฌํ•œ๋‹ค.1. Numpy ๋ฐฐ์—ด ์ €์žฅํ•˜๊ธฐNumpy ๋ฐฐ์—ด์€ ๋‹ค์–‘ํ•œ ํฌ๋งท์œผ๋กœ ์ €์žฅ ๊ฐ€๋Šฅํ•˜๋ฉฐ, ์—ฌ๊ธฐ์„œ๋Š” .npy, .npz, .csv ํฌ๋งท์„ ๋‹ค๋ฃฐ ๊ฒƒ์ž„1.1 .npy ํฌ๋งท์œผ๋กœ ์ €์žฅ.npy ํŒŒ์ผ์€ Numpy์˜ ๊ธฐ๋ณธ์ ์ธ ๋ฐ”์ด๋„ˆ๋ฆฌ ์ €์žฅ ํฌ๋งท์œผ๋กœ, ๋ฐฐ์—ด์˜ ๊ตฌ์กฐ๋ฅผ ๊ทธ๋Œ€๋กœ ์œ ์ง€ํ•˜๋ฉด์„œ ์ €์žฅํ•  ์ˆ˜ ์žˆ์Œimport numpy as nparr = np.array([1, 2, 3, 4, 5])np.save("array.npy", arr)1.2 .npz ํฌ๋งท์œผ๋กœ ์—ฌ๋Ÿฌ ๋ฐฐ์—ด ์ €์žฅ.npz ํŒŒ์ผ์€ ์—ฌ๋Ÿฌ ๊ฐœ์˜ ๋ฐฐ์—ด์„ ํ•œ ๋ฒˆ์— ์ €์žฅํ•  ์ˆ˜ ์žˆ๋Š” ์••์ถ•๋œ Numpy ํฌ๋งท์ž„x = np.arange(10)y = ..

[Python][numpy] Numpy ๊ธฐ์ดˆ๋ถ€ํ„ฐ ํ™œ์šฉ๊นŒ์ง€

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