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2025/02/10 13

[Learn][English] "I'm used to it." vs. "I used to do it." – ํ—ท๊ฐˆ๋ฆฌ๋Š” ์˜์–ด ํ‘œํ˜„ ์™„๋ฒฝ ์ •๋ฆฌ!

๋งŽ์€ ์ด๋“ค์ด "I'm used to it."๊ณผ "I used to do it."์„ ํ˜ผ๋™ํ•œ๋‹ค.๋‘ ํ‘œํ˜„์€ ๋น„์Šทํ•ด ๋ณด์ด์ง€๋งŒ ์˜๋ฏธ๊ฐ€ ์™„์ „ํžˆ ๋‹ค๋ฅด๋‹ค.์ด ๊ธ€์—์„œ ๊ทธ ์ฐจ์ด๋ฅผ ํ™•์‹คํ•˜๊ฒŒ ์ดํ•ดํ•˜๊ณ , ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ์ •๋ฆฌํ•ด๋ณด๊ฒ ๋‹ค.1. "I'm used to it." – (๋‚˜๋Š” ๊ทธ๊ฒƒ์— ์ต์ˆ™ํ•˜๋‹ค.)โœ… ๋œป: ์–ด๋–ค ๊ฒƒ์— ์ต์ˆ™ํ•ด์กŒ์„ ๋•Œ ์‚ฌ์šฉํ•˜๋Š” ํ‘œํ˜„โœ… ๊ตฌ์กฐ: be used to + ๋ช…์‚ฌ(๊ตฌ) / ๋™๋ช…์‚ฌ(-ing)โœ… ์˜๋ฏธ: ์ฒ˜์Œ์—๋Š” ์–ด์ƒ‰ํ–ˆ์ง€๋งŒ, ์ด์ œ๋Š” ์ ์‘ํ•ด์„œ ๊ดœ์ฐฎ์•„์กŒ๋‹ค๋Š” ๋Š๋‚Œ ์˜ˆ๋ฌธ:โœ” I’m used to waking up early. (๋‚˜๋Š” ์ผ์ฐ ์ผ์–ด๋‚˜๋Š” ๊ฒƒ์— ์ต์ˆ™ํ•ด.)โœ” She’s used to spicy food. (๊ทธ๋…€๋Š” ๋งค์šด ์Œ์‹์— ์ต์ˆ™ํ•ด.)โœ” They are used to the cold weather. (๊ทธ..

[Learn][English] "He is funny." vs. "He is fun." – ์ •ํ™•ํ•œ ์˜๋ฏธ์™€ ์ฐจ์ด์ !

๋งŽ์€ ํ•œ๊ตญ์ธ ์˜์–ด ํ•™์Šต์ž๋“ค์ด "fun"๊ณผ "funny"๋ฅผ ํ—ท๊ฐˆ๋ คํ•œ๋‹ค. ํŠนํžˆ "He is funny."์™€ "He is fun."์€ ์–ผํ• ๋ณด๋ฉด ๋น„์Šทํ•˜์ง€๋งŒ ๋œป์ด ์™„์ „ํžˆ ๋‹ค๋ฅด๋‹ค. ๋‘ ํ‘œํ˜„์˜ ์ฐจ์ด๋ฅผ ์ •ํ™•ํžˆ ์ดํ•ดํ•˜๊ณ , ์–ธ์ œ ์–ด๋–ป๊ฒŒ ์‚ฌ์šฉํ•ด์•ผ ํ•˜๋Š”์ง€ ์•Œ์•„๋ณด์ž!1. "He is funny." – ๊ทธ๋Š” ์›ƒ๊ธด(์žฌ๋ฏธ์žˆ๋Š”) ์‚ฌ๋žŒ์ด๋‹ค.โœ… "Funny"๋Š” "์›ƒ๊ธด, ์žฌ๋ฏธ์žˆ๋Š”"์ด๋ผ๋Š” ๋œป์œผ๋กœ, ์ƒ๋Œ€๋ฐฉ์ด ๋†๋‹ด์„ ํ•˜๊ฑฐ๋‚˜ ์œ ๋จธ ๊ฐ๊ฐ์ด ์žˆ์„ ๋•Œ ์‚ฌ์šฉํ•จ.โœ… ์ƒ๋Œ€๋ฐฉ์ด "์‚ฌ๋žŒ๋“ค์„ ์›ƒ๊ฒŒ ๋งŒ๋“œ๋Š”" ๋Šฅ๋ ฅ์„ ๊ฐ€์กŒ๋‹ค๋Š” ์˜๋ฏธ์ž„. ์˜ˆ๋ฌธ:โœ” He is funny. (๊ทธ๋Š” ์›ƒ๊ธด ์‚ฌ๋žŒ์ด์•ผ.)โœ” That comedian is really funny! (์ € ์ฝ”๋ฏธ๋””์–ธ์€ ์ •๋ง ์›ƒ๊ฒจ!)โœ” Your joke was so funny! (๋„ค ๋†๋‹ด ์ง„์งœ ์›ƒ๊ฒผ์–ด!)โœ” She told..

[Learn][English] ์ž์ฃผ ํ‹€๋ฆฌ๋Š” ํ‘œํ˜„ "I will go to home" → "I will go home"

๋งŽ์€ ์ด๋“ค์ด ์˜์–ด๋กœ "์ง‘์— ๊ฐˆ๊ฒŒ." ๋ผ๊ณ  ๋งํ•  ๋•Œ โŒ "I will go to home." ๋ผ๊ณ  ํ‘œํ˜„ํ•˜๋Š”๋ฐ, ์ด๋Š” ๋ฌธ๋ฒ•์ ์œผ๋กœ ํ‹€๋ฆฐ ํ‘œํ˜„์ด๋‹ค.์˜ฌ๋ฐ”๋ฅธ ํ‘œํ˜„์€ โœ… "I will go home." ์™œ "to home"์ด ํ‹€๋ฆฐ ํ‘œํ˜„์ธ์ง€, ๊ทธ๋ฆฌ๊ณ  "home"์„ ์˜ฌ๋ฐ”๋ฅด๊ฒŒ ์‚ฌ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์•Œ์•„๋ณด์ž.1. "I will go to home"์ด ํ‹€๋ฆฐ ์ด์œ ์ผ๋ฐ˜์ ์œผ๋กœ ์žฅ์†Œ๋ฅผ ๋‚˜ํƒ€๋‚ผ ๋•Œ๋Š” "to"๋ฅผ ์‚ฌ์šฉํ•œ๋‹ค.โœ” I will go to the office. (์‚ฌ๋ฌด์‹ค์— ๊ฐˆ ๊ฑฐ์•ผ.)โœ” She went to the store. (๊ทธ๋…€๋Š” ๊ฐ€๊ฒŒ์— ๊ฐ”๋‹ค.)โœ” They are going to the library. (๊ทธ๋“ค์€ ๋„์„œ๊ด€์— ๊ฐ€๊ณ  ์žˆ์–ด.) ๊ทธ๋Ÿฌ๋‚˜ "home"์€ ์žฅ์†Œ ๋ช…์‚ฌ๊ฐ€ ์•„๋‹ˆ๋ผ ๋ถ€์‚ฌ๋กœ ์‚ฌ์šฉ๋˜๊ธฐ ๋•Œ๋ฌธ์— "to"๋ฅผ ๋ถ™์ผ ํ•„์š”๊ฐ€ ์—†๋‹ค.์ฆ‰,..

[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..

[๊ตญ๋‚ด์—ฌํ–‰][์ผ๋ชฐ] ์ถฉ๋‚จ ๋‹น์ง„ ์‚ฝ๊ตํ˜ธ ๋†€์ด๋™์‚ฐ ๊ด€๋žŒ์—ด์ฐจ ์ผ๋ชฐ ์—ฌํ–‰

์ผ์ถœ ์—ฌํ–‰์œผ๋กœ ๋‹น์ง„์„ ์ฐพ์•˜๊ณ , 2024๋…„ ๋งˆ์ง€๋ง‰ ์ผ๋ชฐ์„ ์–ด๋””์„œ ๋ณผ๊นŒ ๊ณ ๋ฏผํ•˜๋˜ ๋„์ค‘ ์‚ฝ๊ตํ˜ธ ๋†€์ด๋™์‚ฐ์— ๊ด€๋žŒ์—ด์ฐจ๊ฐ€ ์žˆ๋Š”๊ฒƒ์„ ๋ฐœ๊ฒฌํ•˜๊ณค ๋ถ€๋ฆฌ๋‚˜์ผ€ ๋‹ฌ๋ ค๊ฐ”๋‹ค. ๋งˆ์Œ์ด ๊ธ‰ํ•ด ์œ ์›์ง€ ์ „์ฒด ์‚ฌ์ง„์„ ์ฐ์ง€ ๋ชปํ–ˆ์ง€๋งŒ ๋‚˜๋ฆ„ ๊ทœ๋ชจ๊ฐ€ ์žˆ์—ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ค‘์š”ํ•œ ๋ฌธ์ œ๋ฅผ ๋†“์ณค์œผ๋‹ˆ  ๋ฐ”๋กœ ์‹์‚ฌ์‹œ๊ฐ„์ด์—ˆ๋‹ค. ๋‹น์ผ ๋ฐฉ๋ฌธํ–ˆ์„๋•Œ ์ €๋… ์‹์‚ฌ ์‹œ๊ฐ„์ด 16:30 ~ 17:30์ด์—ˆ๊ณ , ์ผ๋ชฐ ์˜ˆ์ • ์‹œ๊ฐ„๋„ 17:30์ด์—ˆ๋‹ค. ํ‚ค์˜ค์Šคํฌ๊ฐ€ ์žˆ๋‹ค๋Š” ์•ˆ๋‚ด๋Š” ์žˆ์—ˆ์ง€๋งŒ ์‚ฌ์ง„์ฒ˜๋Ÿผ ๋‹ซํ˜€์žˆ์—ˆ๊ณ , ํ•˜์—ผ์—†์ด ์‹์‚ฌ๊ฐ€ ๋๋‚˜์‹œ๊ธฐ๋ฅผ ๊ธฐ๋‹ค๋ฆด ์ˆ˜ ๋ฐ–์— ์—†๋Š” ์ƒํ™ฉ. ๊ทธ๋ž˜๋„ 17:20๋ถ„ ์ฏ”์Œ ์ง์›๋ถ„์ด ์‹์‚ฌ๋ฅผ ๋งˆ์น˜๊ณ  ์˜ค์…”์„œ ์กฐ๊ธˆ ๋” ์ผ์ฐ ํ‘œ๋ฅผ ๋Š์„ ์ˆ˜ ์žˆ์—ˆ๋‹ค.  ๊ทธ๋ ‡๊ฒŒ ์•„๋‚ด์™€ ์šฐ์—ฌ๊ณก์ ˆ๋์— ๋Œ€๊ด€๋žŒ์ฐจ์— ํƒ‘์Šน ํ•  ์ˆ˜ ์žˆ์—ˆ๋Š”๋ฐ, ๋†€์ด๊ธฐ๊ตฌ๋Š” ์ž˜ ํƒ„๋‹ค๋˜ ์•„๋‚ด๊ฐ€ '๋ผ์ต-, '๋ผ์ต-' ํ•˜๋Š” ์†Œ๋ฆฌ์— ๊ฒ์„ ๋จน๋Š”๊ฒŒ..

[๊ตญ๋‚ด์—ฌํ–‰][์ผ๋ชฐ] ์ถฉ๋‚จ ๋‹น์ง„ ํƒœ์–‘์˜์ฐฝ ์‚ฝ๊ตํ˜ธ ์ผ๋ชฐ ์—ฌํ–‰

2024๋…„ ๋งˆ์ง€๋ง‰ ์ผ๋ชฐ์„ ๋ณด๊ธฐ ์œ„ํ•ด ๋– ๋‚œ ๋‹น์ง„ ์—ฌํ–‰ ์ผ๋ชฐ ์‹œ์ž‘ ์ „ ํƒœ์–‘์˜ ์ฐฝ์ด ๋ณด๊ณ ์‹ถ์–ด์„œ ๋ฐฉ๋ฌธํ•˜์˜€๋Š”๋ฐ, ์ผ๋ชฐ ์‹œ์ž‘ ์ „์ด๋ผ ํ›„๋”ฑ ๋ณด๊ณ  ๋„˜์–ด๊ฐ  ์‚ฌ์ง„์—์„œ ๋ณด์ด๋Š” ๊ฒƒ๋ณด๋‹ค ๊ฐˆ๋งค๊ธฐ๊ฐ€ ํ›จ์”ฌ ๋งŽ์•˜๋Š”๋ฐ, ๊ทธ๋Ÿฌ๋‹ค๋ณด๋‹ˆ ๋ฐ”๋‹ฅ์ด ์™„์ „ ๋˜ฅ๋ฐญ ์ธ๊ทผ ์ฃผ์ฐจ์žฅ์ด ํ˜‘์†Œํ•ด์„œ ์‚ฌ๋žŒ์ด ๋ชฐ๋ฆด๋•Œ๋Š” ์ฃผ์ฐจ๋‚œ์ด ์˜ˆ์ƒ๋˜๋Š” ๊ณณ ๋‹คํ–‰ํžˆ ๋นˆ ์ž๋ฆฌ๊ฐ€ ์žˆ์–ด์„œ ์ฃผ์ฐจ๋Š” ํŽธํžˆ ํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.

[๊ตญ๋‚ด์—ฌํ–‰][์ผ๋ชฐ] ์ถฉ๋‚จ ์„œ์‚ฐ ๊ฐ„์›”์•” ์ƒˆํ•ด๋งž์ด ์ผ๋ชฐ ๋ง›์ง‘ ์—ฌํ–‰

์ƒˆํ•ด๋งž์ด๋กœ ์ฐพ์€ ์ถฉ๋‚จ ์„œ์‚ฐ์— ์žˆ๋Š” ๊ฐ„์›”์•” ๋ฌผ๋•Œ๊ฐ€ ๋งž์ง€ ์•Š์•„ ์•ˆ์œผ๋กœ ์ง์ ‘ ๋“ค์–ด๊ฐ€๋ณด์ง€๋Š” ๋ชปํ–ˆ๋‹ค.  ์ง์ ‘ ๊ฐ„์›”์•”์œผ๋กœ ๋“ค์–ด๊ฐ€ ๋‚ด๋ถ€๋ฅผ ์‚ดํŽด๋ณผ ์ˆ˜๋Š” ์—†์—ˆ์ง€๋งŒ ๋ฉ€๋ฆฌ์„œ ๋ณด๋Š” ๋…ธ์„ ๋งŒ์œผ๋กœ๋„ ์ถฉ๋ถ„ํžˆ ํž๋ง์ด ๋˜๋Š” ๊ฐ„์›”์•”.  ์‚ฌ์‹ค ์„ธ ๋ฒˆ์งธ ๋ฐฉ๋ฌธ์ธ๋ฐ ๋ฌผ๋•Œ์— ๋งž์ถฐ ์˜ค์ง€ ๋ชปํ•ด ์˜ค๋Š˜๋„ ์ด๋ ‡๊ฒŒ ๋ฐ”๋ผ๋งŒ ๋ณด์•˜๋‹ค.  ์ผ์ถœ์€ ์•„๋‹ˆ์ง€๋งŒ ์ƒˆํ•ด ์ฒซ ์ผ๋ชฐ์„ ๋ณด๋ฉฐ ์†Œ์›๋„ ๋นŒ์—ˆ๋Š”๋ฐ, ๋‹ค์Œ์— ๋ฐฉ๋ฌธ ํ• ๋•Œ๋„ ์ด๋ ‡๊ฒŒ ๋‚ ์”จ๊ฐ€ ์ข‹๊ธฐ๋ฅผ,,

[๊ตญ๋‚ด์—ฌํ–‰][๋“ฑ์‚ฐ] ๋•์œ ์‚ฐ ์„ค์ฒœ๋ด‰ '์ƒ์ œ๋ฃจ' ์ „์†Œ ์ „

์ถฅ๋‹ค๊ณ  ๊ฐ€๊นŒ์ด์„œ ๋ชป์ฐ๊ณ  ๋ฉ€๋ฆฌ์„œ๋‚˜๋งˆ ์ฐ์—ˆ๋Š”๋ฐ, ์ด๋ ‡๊ฒŒ ๋  ์ค„ ์•Œ์•˜์œผ๋ฉด ๊ฐ€๊นŒ์ด ๊ฐ€์„œ ํ•œ ์žฅ์ด๋ผ๋„ ์ฐ์„๊ฑธ ๊ทธ๋žฌ๋‚˜๋ณด๋‹ค,,

[Learn][Korean] How to Say "Sorry" in Korean: ๋ฏธ์•ˆํ•ด, ๋ฏธ์•ˆํ•ฉ๋‹ˆ๋‹ค, ์ฃ„์†กํ•ฉ๋‹ˆ๋‹ค, ์ฃ„์†กํ•ด์š”

Apologizing is an important part of any language, and in Korean, there are several ways to say "sorry" depending on the level of formality and the situation. Understanding the differences between ๋ฏธ์•ˆํ•ด, ๋ฏธ์•ˆํ•ฉ๋‹ˆ๋‹ค, ์ฃ„์†กํ•ฉ๋‹ˆ๋‹ค, and ์ฃ„์†กํ•ด์š” will help you use the right expression in different contexts.1. ์ฃ„์†กํ•ฉ๋‹ˆ๋‹ค (joesonghamnida) – The Most Formal "Sorry"โœ… Politeness Level: Very formal (์กด๋Œ“๋ง)โœ… When to Use: In profess..

[Learn][Korean] How to Say "Thank You" in Korean: ๊ณ ๋งˆ์›Œ, ๊ณ ๋งˆ์›Œ์š”, ๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค, ๊ฐ์‚ฌํ•ด์š”

Expressing gratitude is an essential part of any language, and in Korean, there are multiple ways to say "thank you" depending on the level of formality and the situation. Understanding when to use ๊ณ ๋งˆ์›Œ, ๊ณ ๋งˆ์›Œ์š”, ๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค, and ๊ฐ์‚ฌํ•ด์š” will help you sound more natural and polite in different contexts.1. ๊ฐ์‚ฌํ•ฉ๋‹ˆ๋‹ค (gamsahamnida) – The Most Formal "Thank You"โœ… Politeness Level: Very formal (์กด๋Œ“๋ง)โœ… When to Use: In..

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