ํ’€์Šคํƒ ์›น๐ŸŒ ๊ฐœ๋ฐœ์ž ์ง€๋ง์ƒ ๐Ÿง‘๐Ÿฝโ€๐Ÿ’ป
โž• ์ธ๊ณต์ง€๋Šฅ ๊ด€์‹ฌ ๐Ÿค–


Categories


Recent views

  • 1
  • 2
  • 3
  • 4
  • 5

Query ์š”์•ฝ Search Results

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CS์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜-์ƒ

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ •๋ฆฌํŒŒ์ด์ฌ SW๋ฌธ์ œํ•ด๊ฒฐ ๊ธฐ๋ณธList101_์•Œ๊ณ ๋ฆฌ์ฆ˜์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ฐœ์š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด๋ž€ ์œ ํ•œํ•œ ๋‹จ๊ณ„๋ฅผ ํ†ตํ•ด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ ˆ์ฐจ๋‚˜ ๋ฐฉ๋ฒ•1) ์ปดํ“จํ„ฐ ์šฉ์–ด๋กœ ์“ฐ์ด๋ฉฐ, ์ปดํ“จํ„ฐ๊ฐ€ ์–ด๋–ค ์ผ์„ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•œ ๋‹จ๊ณ„์  ๋ฐฉ๋ฒ•2) ์–ด๋– ํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ ˆ์ฐจ ์•Œ๊ณ ๋ฆฌ์ฆ˜...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CS์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜-์ค‘

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜ ์‘์šฉ02 ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋ณต์žก๋„์•Œ๊ณ ๋ฆฌ์ฆ˜ ์œ ํ•œํ•œ ๋‹จ๊ณ„๋ฅผ ํ†ตํ•ด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ ˆ์ฐจ๋‚˜ ๋ฐฉ๋ฒ• ์ฃผ๋กœ ์ปดํ“จํ„ฐ ์šฉ์–ด๋กœ ์“ฐ์ด๋ฉฐ, ์ปดํ“จํ„ฐ๊ฐ€ ์–ด๋–ค ์ผ์„ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•œ ๋‹จ๊ณ„์  ๋ฐฉ๋ฒ• ์–ด๋– ํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ ˆ์ฐจ, ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์“ฐ๋ฉด ๋ฉ”๋ชจ...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CS์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜-ํ•˜

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ „๋ฌธArray ํ™œ์šฉ๋ฏธํŠธ ์ธ ๋” ๋ฏธ๋“ค ์•Œ๊ณ ๋ฆฌ์ฆ˜ (Meet in the middle Algorithm) ๋ถ„ํ•  ์ •๋ณต(Divide and Conquer algorithm)๊ณผ ๋น„์Šทํ•˜๊ฒŒ ์ฃผ์–ด์ง„ input์„ 2๊ฐœ๋กœ ๋‚˜๋ˆˆ ๋’ค, ๋‘๊ฐœ์˜ ์—ฐ์‚ฐ ๊ฒฐ๊ณผ๋ฅผ ์ด์šฉํ•ด ๊ฐ’์„ ์ฐพ์•„...

  • AWS์š”์•ฝCLOUD

    ๐Ÿ“„ AWS๋กœ ์‹œ์ž‘ํ•˜๋Š” ํด๋ผ์šฐ๋“œ ์ปดํ“จํŒ… ์ •๋ฆฌ

    style: numbermin_depth: 2max_depth: 3varied_style: trueAWS๋กœ ์‹œ์ž‘ํ•˜๋Š” ํด๋ผ์šฐ๋“œ ์ปดํ“จํŒ…01 ์•„๋งˆ์กด ์›น ์„œ๋น„์Šค Cloud ๊ฐœ์š”ํด๋ผ์šฐ๋“œ ์ปดํ“จํŒ…(Cloud Computing) ํด๋ผ์šฐ๋“œ ์ปดํ“จํŒ…์ด๋ž€, ์ธํ„ฐ๋„ท ๊ธฐ๋ฐ˜ ์ปดํ“จํŒ…์˜ ์ผ์ข…์œผ๋กœ ๊ตฌ์„ฑ ๊ฐ€๋Šฅํ•œ ์ปดํ“จํŒ… ์ž์›์— ๋Œ€ํ•ด ์–ด๋””์„œ๋‚˜ ์ ‘๊ทผ์ด ๊ฐ€๋Šฅํ•œ, ์ฃผ๋ฌธํ˜•์ ‘๊ทผ์„ ๊ฐ€๋Šฅ์ผ€ ํ•˜๋Š” ...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-Counting

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ์…ˆ(Counting)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction to ...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-ํ•จ์ˆ˜

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ํ•จ์ˆ˜(functions)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction t...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-๊ธฐํ•˜, ์ดํ•ญ ๋ถ„ํฌ

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ๊ธฐํ•˜, ์ดํ•ญ ๋ถ„ํฌ(geometric and binomial distributions)_Introduction to Algorithm, 3rd, Cormen_์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-๊ทธ๋ž˜ํ”„

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ๊ทธ๋ž˜ํ”„(graphs)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction to ...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-ํ–‰๋ ฌ

    ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ํ–‰๋ ฌ (Matrices)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค. ์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction to Algorithm, 3rd, Cormen)์˜ ๋ถ€๋ก์œผ๋กœ ์ทจ๊ธ‰ํ•ด์•ผํ•œ๋‹ค.์ด ์žฅ์—์„œ๋Š” ํ–‰๋ ฌ์˜ ํ‘œ๊ธฐ๋ฒ•,...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-ํ™•๋ฅ 

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ํ™•๋ฅ (Probability)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-ํ™•๋ฅ  ๋ณ€์ˆ˜

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ํ™•๋ฅ  ๋ณ€์ˆ˜(random variables)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Intr...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-๊ด€๊ณ„

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ๊ด€๊ณ„(Relations)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction t...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-์ง‘ํ•ฉ

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ์ง‘ํ•ฉ(Sets)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction to Alg...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-์œ ํ•œํ•ฉ

    ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ์œ ํ•œํ•ฉ(Summation)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction to Algorithm, 3rd, Cormen)์˜ ๋ถ€๋ก์œผ๋กœ ์ทจ๊ธ‰ํ•ด์•ผํ•œ๋‹ค.์œ ํ•œํ•ฉ (Summations...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ๋ณ‘ํ•ฉ ์ •๋ ฌ

    Merge Sort(๋ณ‘ํ•ฉ ์ •๋ ฌ)title: ์ถœ์ฒ˜ _Introduction to Algorithm, 3rd, Cormen_์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค๋ณ‘ํ•ฉ ์ •๋ ฌ์€ divide-and-conquer ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•˜์—ฌ ์žฌ๊ท€์ ์œผ๋กœ ์ •๋ ฌํ•˜๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด๋‹ค.์ „๋ฐ˜์ ์œผ๋กœ ํ€ต์ •๋ ฌ๋ณด๋‹ค ๋’ค๋–จ์–ด์ง€๊ณ  ๋ฐ์ดํ„ฐ ํฌ๊ธฐ ๋งŒํผ ๋ฉ”๋ชจ๋ฆฌ๊ฐ€ ๋” ํ•„์š”ํ•œ๋‹ค.์•ˆ์ •๋œ ์ •๋ ฌ(stable sort)์ด๋ฏ€๋กœ...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CSMATH์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์ˆ˜ํ•™ ๊ธฐ๋ณธ-ํŠธ๋ฆฌ

    style: numbermin_depth: 2max_depth: 3varied_style: true์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์œ„ํ•œ ์ˆ˜ํ•™ - ํŠธ๋ฆฌ(trees)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ผ๋ถ€ ํ‘œ๊ธฐ๋‚˜ ๊ฐœ๋…์ด ๊ธฐ์กด์˜ ์ˆ˜ํ•™๊ณผ ๋‹ค๋ฅผ ์ˆ˜๋„ ์žˆ์œผ๋ฏ€๋กœ, ์—ฌ๊ธฐ์„œ ๋ฐฐ์šด ๋‚ด์šฉ์€ ๋‹จ์ˆœ ํ•ด๋‹น ์ฑ…(Introduction to Al...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CS์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด๋ž€

    ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด๋ž€?์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์ •์˜ ์œ ํ•œํ•œ ๋‹จ๊ณ„๋ฅผ ํ†ตํ•ด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ ˆ์ฐจ๋‚˜ ๋ฐฉ๋ฒ• ์ปดํ“จํ„ฐ๊ฐ€ ๊ณ„์‚ฐ ๋ฌธ์ œ๋ฅผ ์ˆ˜ํ–‰ํ•˜๊ธฐ ์œ„ํ•œ ๋‹จ๊ณ„์  ๋ฐฉ๋ฒ•์ด๋‚˜ ๋„๊ตฌ ์ž…๋ ฅ๊ฐ’์„ ๋ฐ›์•„ ์›ํ•˜๋Š” ์ถœ๋ ฅ๊ฐ’์„ ๋‚ด๋ณด๋‚ด๋Š” ์ž˜ ์ •์˜๋œ ๊ณ„์‚ฐ ๊ณผ์ • ์ฝ”๋“œ ์˜ˆ์‹œ (1~100๊นŒ์ง€ ๋”ํ•˜๋Š” ์ฝ”๋“œ์˜ 2๊ฐ€์ง€ ๋ฐฉ๋ฒ•)def calcSum(n) : sum = 0 for i in ...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CS์š”์•ฝ

    ๐Ÿ“„ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์„ฑ๋Šฅ ๋ถ„์„

    ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์„ฑ๋Šฅ ๋ถ„์„title: ์ถœ์ฒ˜ Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์•Œ๊ณ ๋ฆฌ์ฆ˜ ๋น„์šฉ์—๋Š” ๋ฉ”๋ชจ๋ฆฌ, ํ†ต์‹  ๋Œ€์—ญํญ, ํ•„์š” ํ•˜๋“œ์›จ์–ด ๋“ฑ์ด ์žˆ๊ฒ ์ง€๋งŒ, ๊ฐ€์žฅ ์ค‘์š”์‹œ ์—ฌ๊ธฐ๋Š” ์ž์› ๊ธฐ์ค€์€ ์—ญ์‹œ ์—ฐ์‚ฐ ์‹œ๊ฐ„์ด๋‹ค.์‚ฌ์‹ค, ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ์„ฑ๋Šฅ์€ ์ž…๋ ฅ ๊ฐ’, ์ปดํ“จํ„ฐ์˜ ๊ตฌ์กฐ, ์‚ฌ์šฉ์ž์˜ ๋ชฉ์ ์— ๋”ฐ๋ผ ๋‹ค๋ฅด๊ฒŒ ํ‰๊ฐ€๋  ์ˆ˜ ์žˆ์ง€๋งŒ, ...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CS์š”์•ฝ

    ๐Ÿ“„ ์‹œ๊ฐ„ ๋ณต์žก๋„

    ์‹œ๊ฐ„ ๋ณต์žก๋„(Time complexity)Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์•ž์„œ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ์—ฐ์‚ฐ ๋น„์šฉ ๊ตฌํ•˜๊ธฐ ๊ธ€์„ ๋ณด๊ณ  ์˜ค๋Š” ๊ฒƒ์„ ์ถ”์ฒœ์‹œ๊ฐ„ ๋ณต์žก๋„(Time complexity)๋ž€?์‹œ๊ฐ„๋ณต์žก๋„๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š”๋ฐ ๊ฑธ๋ฆฌ๋Š” ์‹œ๊ฐ„๊ณผ ์ž…๋ ฅ์˜ ํ•จ์ˆ˜ ๊ด€๊ณ„๋ฅผ ์ ๊ทผ์ ์ธ ํ‘œ๊ธฐ๋ฒ•์œผ๋กœ ๋‚˜ํƒ€๋‚ด์–ด ์ •๋Ÿ‰ํ™”ํ•œ ๊ฒƒ์ด๋‹ค...

  • ์•Œ๊ณ ๋ฆฌ์ฆ˜CS์š”์•ฝ

    ๐Ÿ“„ ๋ฃจํ”„ ๋ถˆ๋ณ€์„ฑ

    ๋ฃจํ”„ ๋ถˆ๋ณ€์„ฑ(Loop Invariant) Introduction to Algorithm, 3rd, Cormen์„ ํ† ๋Œ€๋กœ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.๋ฃจํ”„ ๋ถˆ๋ณ€์„ฑ์˜ ์ •์˜์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ํƒ€๋‹นํ•œ์ง€ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ์‚ฌ์šฉ๋˜๋Š” ์„ฑ์งˆ๋กœ, ๋ฃจํ”„ ๋ถˆ๋ณ€์„ฑ์„ ์ •์˜ํ•˜๊ณ  ๋ฃจํ”„๊ฐ€ ์ œ๋Œ€๋กœ ๋Œ์•„๊ฐ€๋Š” ๋™์•ˆ ๋ฃจํ”„ ๋ถˆ๋ณ€์„ฑ์ด ๋ณ€ํ•˜์ง€ ์•Š์Œ์„ ํ™•์ธํ•จ์œผ๋กœ์จ, ๊ตฌํ˜„ ์•Œ๊ณ ๋ฆฌ์ฆ˜์ด ์˜ณ์€์ง€ ์ ๊ฒ€ํ•˜๋Š” ๋ฐ ๋„์›€์„ ์ค„ ์ˆ˜ ์žˆ๋‹ค...

  • OSCS์ปดํ“จํ„ฐ_๊ตฌ์กฐ์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 1-์ปดํ“จํ„ฐ ์‹œ์Šคํ…œ์˜ ์†Œ๊ฐœ

    style: numbermin_depth: 2max_depth: 3varied_style: true1. ์ปดํ“จํ„ฐ ์‹œ์Šคํ…œ์˜ ์†Œ๊ฐœtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01 ์ปดํ“จํ„ฐ ํ•˜๋“œ์›จ์–ด์˜ ๊ตฌ์„ฑ์ปดํ“จํ„ฐ ์‹œ์Šคํ…œ์€ ๋‹ค์Œ ๋‘ ๊ฐ€์ง€๋กœ ์ด๋ฃจ์–ด์ง„๋‹ค. ๋ฐ์ดํ„ฐ๋ฅผ ์ฒ˜๋ฆฌํ•˜๋Š” ๋ฌผ๋ฆฌ์ ์ธ ๊ธฐ๊ณ„์žฅ์น˜ ํ•˜๋“œ์›จ์–ด(h...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 2-์šด์˜์ฒด์ œ๋ž€

    style: numbermin_depth: 2max_depth: 3varied_style: true2. ์šด์˜์ฒด์ œ๋ž€?title: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์šด์˜ ์ฒด์ œ(Operating System)๋ž€ ์‚ฌ์šฉ์ž๋ฅผ ์œ„ํ•ด ์‘์šฉ ํ”„๋กœ๊ทธ๋žจ ๋™์ž‘์˜ ํ™˜๊ฒฝ์™€ ํŽธ์˜์„ฑ์„ ์ œ๊ณตํ•˜๋ฉฐ, ํ•˜๋“œ์›จ์–ด์™€ ์ปดํ“จํ„ฐ ์ž์›...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 3-ํ”„๋กœ์„ธ์Šค์™€ ์Šค๋ ˆ๋“œ

    3. ํ”„๋กœ์„ธ์Šค์™€ ์Šค๋ ˆ๋“œtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.ํ”„๋กœ์„ธ์Šค์˜ ๊ฐœ๋…๊ณผ ์ƒํƒœ ๋ณ€ํ™”ํ”„๋กœ์„ธ์Šค(process)๋ž€?ํ”„๋กœ์„ธ์Šค(process) ๋˜๋Š” ์ž‘์—…(task)๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์ด ์—ฌ๋Ÿฌ ์˜๋ฏธ๋กœ ์ •์˜ ๋œ๋‹ค. ์ฃผ์†Œ ๊ณต๊ฐ„์„ ๊ฐ€์ง€๊ณ  ์‹คํ–‰ ์ค‘์ธ ํ”„๋กœ๊ทธ๋žจ ๋น„๋™๊ธฐ์  ํ–‰์œ„ ...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 4-๋ณ‘ํ–‰ ํ”„๋กœ์„ธ์Šค์™€ ์ƒํ˜ธ๋ฐฐ์ œ

    4. ๋ณ‘ํ–‰ ํ”„๋กœ์„ธ์Šค์™€ ์ƒํ˜ธ๋ฐฐ์ œtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.๋ณ‘ํ–‰ ํ”„๋กœ์„ธ์Šค๋ณ‘ํ–‰ ํ”„๋กœ์„ธ์Šค๋ž€?ํ”„๋กœ์„ธ์Šค๋Š” ํ”„๋กœ์„ธ์„œ, ๋ ˆ์ง€์Šคํ„ฐ, ์บ์‹œ, ์ž…์ถœ๋ ฅ ์žฅ์น˜ ๋“ฑ ์—ฌ๋Ÿฌ ์ž์›์„ ์‚ฌ์šฉํ•˜๋ฉฐ, ์ด์ค‘, ๋ฉ”๋ชจ๋ฆฌ ๊ฐ™์€ ์ž์›์€ ๋ชจ๋“  ํ”„๋กœ์„ธ์Šค๊ฐ€ ๋™์‹œ์— ๋ณ‘๋ ฌ๋กœ ๊ณต์œ ํ”„๋กœ์„ธ์„œ ์ž์›์„ ์‹œ๋ถ„ํ• ์„ ํ†ตํ•ด ์—ฌ๋Ÿฌ ํ”„๋กœ์„ธ์„œ๊ฐ€ ...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 5-๊ต์ฐฉ ์ƒํƒœ์™€ ๊ธฐ์•„ ์ƒํƒœ

    style: numbermin_depth: 2max_depth: 3varied_style: true5. ๊ต์ฐฉ ์ƒํƒœ์™€ ๊ธฐ์•„ ์ƒํƒœtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.๊ต์ฐฉ ์ƒํƒœ์˜ ๊ฐœ๋…๊ณผ ๋ฐœ์ƒ ์›์ธ1 ๊ต์ฐฉ ์ƒํƒœ(deadlock)์˜ ๊ฐœ๋…๊ต์ฐฉ ์ƒํƒœ ์ •์˜ ์‹œ์Šคํ…œ ์ž์›์— ์š”๊ตฌ๊ฐ€ ๋’ค์—‰ํ‚จ...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 6-ํ”„๋กœ์„ธ์Šค ์Šค์ผ€์ค„๋ง

    style: numbermin_depth: 2max_depth: 3varied_style: true6. ํ”„๋กœ์„ธ์Šค ์Šค์ผ€์ค„๋งtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์Šค์ผ€์ค„๋ง์˜ ์ดํ•ด1 ์Šค์ผ€์ค„๋ง์˜ ๊ฐœ๋…์Šค์ผ€์ค„๋ง(scheduling)์€ ๋‹ค์Œ์„ ์˜๋ฏธํ•œ๋‹ค. ๋‹ค์ค‘ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ํ™˜๊ฒฝ์—์„œ ํ”„๋กœ์„ธ์„œ...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 7-๋ฉ”๋ชจ๋ฆฌ ๊ด€๋ฆฌ

    style: numbermin_depth: 2max_depth: 3varied_style: true7. ๋ฉ”๋ชจ๋ฆฌ ๊ด€๋ฆฌtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01 ๋ฉ”๋ชจ๋ฆฌ ๊ด€๋ฆฌ์˜ ๊ฐœ์š”1 ๋ฉ”๋ชจ๋ฆฌ ๊ด€๋ฆฌ์˜ ๊ฐœ๋…๊ณผ ์ •์ฑ…๋ฉ”๋ชจ๋ฆฌ๋ž€ ๋””์Šคํฌ์— ์žˆ๋˜ ํ”„๋กœ๊ทธ๋žจ์„ ์ ์žฌํ•˜์—ฌ ์‹คํ–‰ํ•˜๋Š” ์ž‘์—… ๊ณต๊ฐ„๋ฉ”๋ชจ๋ฆฌ ๊ด€๋ฆฌ๋Š” ํ”„...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 8-๊ฐ€์ƒ ๋ฉ”๋ชจ๋ฆฌ

    style: numbermin_depth: 2max_depth: 3varied_style: true8. ๊ฐ€์ƒ ๋ฉ”๋ชจ๋ฆฌtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01 ๊ฐ€์ƒ ๋ฉ”๋ชจ๋ฆฌ์˜ ์ดํ•ด์‚ฌ์šฉ์ž์™€ ๋…ผ๋ฆฌ์  ์ฃผ์†Œ๋ฅผ ๋ฌผ๋ฆฌ์ ์œผ๋กœ ๋ถ„๋ฆฌํ•ด ์‚ฌ์šฉ์ž๊ฐ€ ๋ฉ”์ธ ๋ฉ”๋ชจ๋ฆฌ ์šฉ๋Ÿ‰์„ ์ดˆ๊ณผํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ๋ณด์กฐ ๊ธฐ์–ต์žฅ์น˜์— ํ• ๋‹น...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 9-์ž…์ถœ๋ ฅ ์‹œ์Šคํ…œ๊ณผ ๋””์Šคํฌ ๊ด€๋ฆฌ

    style: numbermin_depth: 2max_depth: 3varied_style: true9. ์ž…์ถœ๋ ฅ ์‹œ์Šคํ…œtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01 ์ž…์ถœ๋ ฅ ์‹œ์Šคํ…œ ๊ด€๋ฆฌ1 ์ž…์ถœ๋ ฅ ์‹œ์Šคํ…œ๊ณผ ์ž…์ถœ๋ ฅ ๋ชจ๋“ˆ์ž…์ถœ๋ ฅ ์‹œ์Šคํ…œ์€ ๋ชจ๋‹ˆํ„ฐ, ํ‚ค๋ณด๋“œ ๊ฐ™์€ ํ•˜๋“œ์›จ์–ด์ธ ์ž…์ถœ๋ ฅ ์žฅ์น˜์™€ ์ž…์ถœ๋ ฅ ๋ชจ๋“ˆ...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 10-ํŒŒ์ผ ๊ด€๋ฆฌ

    style: numbermin_depth: 2max_depth: 3varied_style: true10. ํŒŒ์ผ ๊ด€๋ฆฌtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01 ํŒŒ์ผ ์‹œ์Šคํ…œ๊ณผ ํŒŒ์ผ1 ํŒŒ์ผ ์‹œ์Šคํ…œ์˜ ๊ฐœ๋…์ •๋ณด๋ฅผ ์ €์žฅํ•˜๋Š” ๋…ผ๋ฆฌ์ ์ธ ๊ด€์ ๊ณผ ์ €์žฅ์žฅ์น˜์˜ ๋ฌผ๋ฆฌ์ ์ธ ํŠน์„ฑ์„ ๊ณ ๋ คํ•ด ๋…ผ๋ฆฌ์  ์ €์žฅ ๋‹จ์œ„์ธ...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 11-๋ถ„์‚ฐ ๋ฐ ๋‹ค์ค‘(๋ณ‘๋ ฌ) ์ฒ˜๋ฆฌ ์‹œ์Šคํ…œ

    style: numbermin_depth: 2max_depth: 3varied_style: true11. ๋ถ„์‚ฐ ๋ฐ ๋‹ค์ค‘(๋ณ‘๋ ฌ) ์ฒ˜๋ฆฌ ์‹œ์Šคํ…œtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01 ๋ถ„์‚ฐ ์‹œ์Šคํ…œ1 ๋„คํŠธ์›Œํฌ์™€ ๋ถ„์‚ฐ ์‹œ์Šคํ…œ๋ถ„์‚ฐ ์ฒ˜๋ฆฌ ์ปดํ“จํ„ฐ ์‚ฌ์šฉ์ž ๊ฐ„์— ์„œ๋กœ์˜ ์ž์›, ์žฅ์น˜, ๋ฐ์ดํ„ฐ๋ฅผ ๊ต...

  • OSCS์š”์•ฝ

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 12-์‹œ์Šคํ…œ ๋ณด์•ˆ๊ณผ ๋ณด์•ˆ ์šด์˜์ฒด์ œ

    style: numbermin_depth: 2max_depth: 3varied_style: true12. ์‹œ์Šคํ…œ ๋ณด์•ˆ๊ณผ ๋ณด์•ˆ ์šด์˜์ฒด์ œtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01 ๋ณด์•ˆ์˜ ๊ฐœ๋…๊ณผ ๋ณด์•ˆ ์œ„ํ˜‘์˜ ์œ ํ˜•1 ๋ณด์•ˆ์˜ ๊ฐœ๋… ๋ณดํ˜ธ: ์ปดํ“จํ„ฐ ์‹œ์Šคํ…œ์— ์ €์žฅ๋œ ํ”„๋กœ๊ทธ๋žจ๊ณผ ๋ฐ์ดํ„ฐ ์•ก์„ธ์Šค ์ œ...

  • OSCS์š”์•ฝCRUDEHIDE

    ๐Ÿ“„ OS ์ •๋ฆฌ-Chap 13-์œ ๋‹‰์Šค ์šด์˜์ฒด์ œ

    style: numbermin_depth: 2max_depth: 3varied_style: true13. ์œ ๋‹‰์Šค ์šด์˜์ฒด์ œtitle: ์ถœ์ฒ˜ IT COOK BOOK ์šด์˜์ฒด์ œ (๊ฐœ์ • 3ํŒ, ๊ตฌํ˜„ํšŒ ์ €, ํ•œ๋น› ์•„์นด๋ฐ๋ฏธ)๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01 ์œ ๋‹‰์Šค์˜ ํƒ„์ƒ๊ณผ ๊ตฌ์„ฑ1 ์œ ๋‹‰์Šค์˜ ํƒ„์ƒ๊ณผ ๋ฐœ์ „ ๊ณผ์ •2 ์œ ๋‹‰์Šค์˜ ์„ค๊ณ„ ์›์น™3 ์œ ๋‹‰์Šค์˜ ํŠน์ง•4 ์œ ๋‹‰์Šค์˜ ๊ตฌ์„ฑ ์š”์†Œ4.1 ์ปค๋„...

  • CSNETWORK์š”์•ฝ

    ๐Ÿ“„ ๋„คํŠธ์›Œํฌ ์ •๋ฆฌ-Chap 1-์ปดํ“จํ„ฐ ๋„คํŠธ์›Œํฌ์™€ ์ธํ„ฐ๋„ท

    Chapter 1. ์ปดํ“จํ„ฐ ๋„คํŠธ์›Œํฌ์™€ ์ธํ„ฐ๋„ท (Computer network and Internet)style: numbermin_depth: 2max_depth: 3varied_style: truetitle: ์ถœ์ฒ˜ Computer Networking: A Top-Down Approach(Jim Kurose, Keith Ross)์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ...

  • CSNETWORK์š”์•ฝ

    ๐Ÿ“„ ๋„คํŠธ์›Œํฌ ์ •๋ฆฌ-Chap 2-์‘์šฉ ๊ณ„์ธต

    style: numbermin_depth: 2max_depth: 3varied_style: truetitle: ์ถœ์ฒ˜ Computer Networking: A Top-Down Approach(Jim Kurose, Keith Ross)์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.(Jim Kurose Homepage) student resources : Companion W...

  • CSNETWORK์š”์•ฝ

    ๐Ÿ“„ ๋„คํŠธ์›Œํฌ ์ •๋ฆฌ-Chap 3-์ „๋‹ฌ ๊ณ„์ธต

    Chapter 3. ์ „๋‹ฌ ๊ณ„์ธต(Transport Layer)style: numbermin_depth: 2max_depth: 3varied_style: truetitle: ์ถœ์ฒ˜ Computer Networking: A Top-Down Approach(Jim Kurose, Keith Ross)์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.(Jim Kurose Homepage)...

  • CSNETWORK์š”์•ฝ

    ๐Ÿ“„ ๋„คํŠธ์›Œํฌ ์ •๋ฆฌ-Chap 4-๋„คํŠธ์›Œํฌ ๊ณ„์ธต-๋ฐ์ดํ„ฐ ์ธก๋ฉด

    Chapter 4. ๋„คํŠธ์›Œํฌ ๊ณ„์ธต: ๋ฐ์ดํ„ฐ ์ธก๋ฉด(Network Layer: Data plane)style: numbermin_depth: 2max_depth: 3varied_style: truetitle: ์ถœ์ฒ˜ Computer Networking: A Top-Down Approach(Jim Kurose, Keith Ross)์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.(...

  • CSNETWORK์š”์•ฝ

    ๐Ÿ“„ ๋„คํŠธ์›Œํฌ ์ •๋ฆฌ-Chap 5-๋„คํŠธ์›Œํฌ ๊ณ„์ธต-์ปจํŠธ๋กค ์ธก๋ฉด

    Chapter 5. ๋„คํŠธ์›Œํฌ ๊ณ„์ธต: ์ปจํŠธ๋กค ์ธก๋ฉด(Network Layer: Control plane)style: numbermin_depth: 2max_depth: 3varied_style: truetitle: ์ถœ์ฒ˜ Computer Networking: A Top-Down Approach(Jim Kurose, Keith Ross)์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ...

  • CSNETWORK์š”์•ฝ

    ๐Ÿ“„ ๋„คํŠธ์›Œํฌ ์ •๋ฆฌ-Chap 6-์—ฐ๊ฒฐ ๊ณ„์ธต๊ณผ LAN

    Chapter 6. ์—ฐ๊ฒฐ ๊ณ„์ธต๊ณผ LAN(Link Layer and LAN)style: numbermin_depth: 2max_depth: 3varied_style: truetitle: ์ถœ์ฒ˜ Computer Networking: A Top-Down Approach(Jim Kurose, Keith Ross)์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.(Jim Kurose H...

  • CSNETWORK์š”์•ฝ

    ๐Ÿ“„ ๋„คํŠธ์›Œํฌ ์ •๋ฆฌ-Chap 7-๋ฌด์„ ๊ณผ ๋ชจ๋ฐ”์ผ ๋„คํŠธ์›Œํฌ

    Chapter 7. ๋ฌด์„ ๊ณผ ๋ชจ๋ฐ”์ผ ๋„คํŠธ์›Œํฌ(Wireless and Mobile Networks)style: numbermin_depth: 2max_depth: 3varied_style: truetitle: ์ถœ์ฒ˜ Computer Networking: A Top-Down Approach(Jim Kurose, Keith Ross)์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.(...

  • CSNETWORK์š”์•ฝ

    ๐Ÿ“„ ๋„คํŠธ์›Œํฌ ์ •๋ฆฌ-Chap 8-์ปดํ“จํ„ฐ ๋„คํŠธ์›Œํฌ ๋ณด์•ˆ

    Chapter 8. ์ปดํ“จํ„ฐ ๋„คํŠธ์›Œํฌ์—์„œ์˜ ๋ณด์•ˆ(Security in Computer Networks)style: numbermin_depth: 2max_depth: 3varied_style: truetitle: ์ถœ์ฒ˜ Computer Networking: A Top-Down Approach(Jim Kurose, Keith Ross)์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ...

  • AIDL์š”์•ฝ

    ๐Ÿ“„ ๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ณธ

    style: numbermin_depth: 2max_depth: 3varied_style: true๋”ฅ๋Ÿฌ๋‹ ๊ธฐ๋ณธ(Deep learning Basic) ๋ณธ ์ž๋ฃŒ๋Š” Naver BoostAI camp์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹คHistorical Review์†Œ๊ฐœ ๊ตฌํ˜„(์ฝ”๋”ฉ) ์‹ค๋ ฅ, ์ˆ˜ํ•™ ์Šคํ‚ฌ, ์ตœ์‹  ๋…ผ๋ฌธ ๊ธฐ์ˆ  ๋“ฑ์˜ ๋Šฅ๋ ฅ์ด ์ค‘์š”ํ•˜๋‹ค.[img 0. ์ธ๊ณต์ง€๋Šฅ์˜ ๋Œ€๋ถ„๋ฅ˜...

  • AIDATA_VISDATA์š”์•ฝ

    ๐Ÿ“„ ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๊ธฐ๋ณธ

    style: numbermin_depth: 2max_depth: 3varied_style: true๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๊ธฐ๋ณธ๋ฐ์ดํ„ฐ๋ฅผ ๊ทธ๋ž˜ํ”ฝ ์š”์†Œ๋กœ ๋งคํ•‘ํ•˜์—ฌ ์‹œ๊ฐ์ ์œผ๋กœ ํ‘œํ˜„ํ•˜๋Š” ๊ฒƒ์‹œ๊ฐํ™”์˜ ๋‹ค์–‘ํ•œ ๊ณ ๋ ค ์š”์†Œ ๋ชฉ์  : ์™œ ์‹œ๊ฐํ™” ํ•˜๋Š”๊ฐ€? ๋…์ž : ์‹œ๊ฐํ™” ๊ฒฐ๊ณผ๋Š” ๋ˆ„๊ตฌ๋ฅผ ์œ„ํ•œ ๊ฒƒ์ธ๊ฐ€? ๋ฐ์ดํ„ฐ : ์–ด๋–ค ๋ฐ์ดํ„ฐ๋ฅผ ์‹œ๊ฐํ™”ํ•  ๊ฒƒ์ธ๊ฐ€? ์Šคํ† ๋ฆฌ : ์–ด๋–ค ํ๋ฆ„์œผ๋กœ ์ธ์‚ฌ์ดํŠธ๋ฅผ ์ „...

  • AIGRAPH์š”์•ฝ

    ๐Ÿ“„ ๊ทธ๋ž˜ํ”„ ๊ธฐ๋ณธ

    style: numbermin_depth: 2max_depth: 3varied_style: true๊ทธ๋ž˜ํ”„(Graph) ๊ธฐ๋ณธ ๋„ค์ด๋ฒ„ boostcamp AI Tech์˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค์ •์  ์ง‘ํ•ฉ๊ณผ ๊ฐ„์„  ์ง‘ํ•ฉ์œผ๋กœ ์ด๋ฃจ์–ด์ง„ ์ˆ˜ํ•™์  ๊ตฌ์กฐ๋กœ, ๋‹ค์–‘ํ•œ ๋ณต์žก๊ณ„(Complex Network)๋ฅผ ๋ถ„์„ํ•  ์ˆ˜ ์žˆ๋Š” ์–ธ์–ดGraph IntroductionGraph๋ž€ ๋ฌด์—‡์ด...

  • AI๋ชจ๋ธ_๊ฒฝ๋Ÿ‰ํ™”์š”์•ฝ

    ๐Ÿ“„ ๋ชจ๋ธ ๊ฒฝ๋Ÿ‰ํ™” ๊ธฐ๋ณธ

    style: numbermin_depth: 2max_depth: 3varied_style: true๋ชจ๋ธ ๊ฒฝ๋Ÿ‰ํ™”(Lightweight) ๊ธฐ๋ณธ Naver AI boostcamp ๋‚ด์šฉ์„ ์ •๋ฆฌํ•˜์˜€์Šต๋‹ˆ๋‹ค.Lightweight model ๊ฐœ์š”1. ๊ฒฐ์ • (Decision making)์—ฐ์—ญ์  (deductive) ๊ฒฐ์ •์ด๋ฏธ ์ฐธ์œผ๋กœ ์ฆ๋ช…(Axiom)๋˜๊ฑฐ๋‚˜ ์ •์˜๋ฅผ ํ†ตํ•˜์—ฌ ๋…ผ...

  • AINLPMRC์š”์•ฝ

    ๐Ÿ“„ ๊ธฐ๊ณ„ ๋…ํ•ด ๊ธฐ๋ณธ

    style: numbermin_depth: 2max_depth: 3varied_style: true๊ธฐ๊ณ„ ๋…ํ•ด(MRC) ๊ธฐ๋ณธ Naver AI boostcamp ๊ธฐ๊ณ„ ๋…ํ•ด ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.1. MRC Intro & Python BasicsIntroduction to MRCMachine Reading Comprehension(MRC. ๊ธฐ๊ณ„๋…ํ•ด)...

  • AINLP์š”์•ฝ

    ๐Ÿ“„ ์ž์—ฐ์–ด์ฒ˜๋ฆฌ ๊ธฐ๋ณธ

    style: numbermin_depth: 2max_depth: 3varied_style: true์ž์—ฐ์–ด์ฒ˜๋ฆฌ(Natural Language Processing, NLP) ๊ธฐ๋ณธ NAVER AI boost camp ์ˆ˜์—…์„ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.Intro to Natural Language Processing(NLP) ์ปดํ“จํ„ฐ๊ฐ€ ์ฃผ์–ด์ง„ ๋‹จ์–ด๋‚˜ ๋ฌธ์žฅ, ๋ฌธ๋‹จ, ๊ธ€์„ ...

  • AINLP์š”์•ฝ

    ๐Ÿ“„ ํ•œ๊ตญ์–ด ์–ธ์–ด ๋ชจ๋ธ ๋‹ค๋ฃจ๊ธฐ-KLUE

    style: numbermin_depth: 2max_depth: 3varied_style: trueKLUE(ํ•œ๊ตญ์–ด ์–ธ์–ด ๋ชจ๋ธ ํ•™์Šต ๋ฐ ๋‹ค์ค‘ ๊ณผ์ œ ํŠœ๋‹) Naver AI Boostcamp์˜ KLUE ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.01. ์ธ๊ณต์ง€๋Šฅ๊ณผ ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ์ธ๊ณต์ง€๋Šฅ๊ณผ ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ์— ๋Œ€ํ•˜์—ฌ์ธ๊ณต์ง€๋Šฅ : ์ธ๊ฐ„์˜ ์ง€๋Šฅ์ด ๊ฐ€์ง€๋Š” ํ•™์Šต, ์ถ”๋ฆฌ, ์ ์‘, ๋…ผ์ฆ ๋”ฐ์œ„์˜ ๊ธฐ๋Šฅ์„ ...

  • AI์ •ํ˜•๋ฐ์ดํ„ฐ์š”์•ฝ

    ๐Ÿ“„ DKT ๊ธฐ๋ณธ

    style: numbermin_depth: 2max_depth: 3varied_style: true์‹ฌ์ธต ์ง€์‹ ํƒ์ƒ‰(Deep Knowledge Tracing, DKT) ๊ธฐ๋ณธ Naver AI boostcamp DKT ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.DKT ์ดํ•ด ๋ฐ DKT Trend ์†Œ๊ฐœDKT Task ์ดํ•ดDKT (DEEP KNOWLEDGE TRACING) : ๋”ฅ๋Ÿฌ๋‹...

  • AI์ •ํ˜•๋ฐ์ดํ„ฐ์š”์•ฝ

    ๐Ÿ“„ ์ •ํ˜• ๋ฐ์ดํ„ฐ ๋ถ„๋ฅ˜ ๊ธฐ๋ณธ

    style: numbermin_depth: 2max_depth: 3varied_style: true์ •ํ˜• ๋ฐ์ดํ„ฐ ๋ถ„๋ฅ˜ ๊ธฐ๋ณธ Naver AI Boostcamp์˜ ์ •ํ˜• ๋ฐ์ดํ„ฐ ๋ถ„๋ฅ˜ ๊ฐ•์˜๋ฅผ ์ •๋ฆฌํ•œ ๋‚ด์šฉ์ž…๋‹ˆ๋‹ค.์ •ํ˜• ๋ฐ์ดํ„ฐ์™€ ๋ฐ์ดํ„ฐ์˜ ์ดํ•ด์ •ํ˜• ๋ฐ์ดํ„ฐ๋ž€, ์—‘์…€ ํŒŒ์ผ์ด๋‚˜ ๊ด€๊ณ„ํ˜• ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค์˜ ํ…Œ์ด๋ธ”์— ๋‹ด์„ ์ˆ˜ ์žˆ๋Š” ๋ฐ์ดํ„ฐ๋กœ ํ–‰(row)๊ณผ ์—ด(column)์œผ๋กœ ํ‘œํ˜„ ๊ฐ€๋Šฅ...