JMP์šฉ ํ™•์žฅ ๊ฒ€์ƒ‰

์ถ”์ฒœ

์–ด์‹œ์Šคํ„ดํŠธ. ์ผ๋ฐ˜์ ์œผ๋กœ ์‚ฌ์šฉ๋˜๋Š” LLM์„ ์‚ฌ์šฉํ•˜์—ฌ ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด JSL ์ž‘์„ฑ, ๋ถ„์„ ์‹คํ–‰, ๋ฐ์ดํ„ฐ ํƒ์ƒ‰ ๋“ฑ์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ•๋ ฅํ•˜๊ณ  ์œ ์—ฐํ•œ JMP ์šฉ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Utility, Machine Learning. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 3 / 5. 553 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์–ด์‹œ์Šคํ„ดํŠธ

์ผ๋ฐ˜์ ์œผ๋กœ ์‚ฌ์šฉ๋˜๋Š” LLM์„ ์‚ฌ์šฉํ•˜์—ฌ ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด JSL ์ž‘์„ฑ, ๋ถ„์„ ์‹คํ–‰, ๋ฐ์ดํ„ฐ ํƒ์ƒ‰ ๋“ฑ์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ•๋ ฅํ•˜๊ณ  ์œ ์—ฐํ•œ JMP ์šฉ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค.

๋จธ์‹  ๋Ÿฌ๋‹, ์œ ํ‹ธ๋ฆฌํ‹ฐ

553 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

JMPยฎ Pro์šฉ XGBoost. ์˜ˆ์ธก ๋ชจ๋ธ๋ง์„ ์œ„ํ•œ ์ธ๊ธฐ ์˜คํ”ˆ ์†Œ์Šค ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ XGBoost์˜ ํฌ์ธํŠธ ์•ค ํด๋ฆญ ์ธํ„ฐํŽ˜์ด์Šค. ๋ฒ”์ฃผ: Data Science, Machine Learning. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 802 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

JMPยฎ Pro์šฉ XGBoost

์˜ˆ์ธก ๋ชจ๋ธ๋ง์„ ์œ„ํ•œ ์ธ๊ธฐ ์˜คํ”ˆ ์†Œ์Šค ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ XGBoost์˜ ํฌ์ธํŠธ ์•ค ํด๋ฆญ ์ธํ„ฐํŽ˜์ด์Šค

๋ฐ์ดํ„ฐ ๊ณผํ•™, ๋จธ์‹  ๋Ÿฌ๋‹

802 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

JSL-Hamcrest. JSL๋กœ ํ‘œํ˜„๋ ฅ์ด ํ’๋ถ€ํ•œ ํ…Œ์ŠคํŠธ๋ฅผ ์ž‘์„ฑํ•˜๊ธฐ ์œ„ํ•œ ํ”„๋ ˆ์ž„์›Œํฌ. ๋ฒ”์ฃผ: Utility. JMP์—์„œ ์ œ์ž‘. 77 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

JSL-Hamcrest

JSL๋กœ ํ‘œํ˜„๋ ฅ์ด ํ’๋ถ€ํ•œ ํ…Œ์ŠคํŠธ๋ฅผ ์ž‘์„ฑํ•˜๊ธฐ ์œ„ํ•œ ํ”„๋ ˆ์ž„์›Œํฌ

์œ ํ‹ธ๋ฆฌํ‹ฐ

77 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

S3 ๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ. Amazon S3์—์„œ ๋ฐ์ดํ„ฐ ๊ฐ€์ ธ์˜ค๊ธฐ ๋ฐ ์ฟผ๋ฆฌํ•˜๊ธฐ. ๋ฒ”์ฃผ: Data Connectors. JMP์—์„œ ์ œ์ž‘. 94 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

S3 ๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ

Amazon S3์—์„œ ๋ฐ์ดํ„ฐ ๊ฐ€์ ธ์˜ค๊ธฐ ๋ฐ ์ฟผ๋ฆฌํ•˜๊ธฐ

๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ

94 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ตœ๋‹ค ๋‹ค์šด๋กœ๋“œ

ํ•™์ƒ ๋ฉ”๋‰ด. ํ•ต์‹ฌ ํ†ต๊ณ„ ๊ฐœ๋…์„ ๊ต์œกํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๋Œ€ํ™”์‹ ์• ํ”Œ๋ฆฟ์ด ํฌํ•จ๋œ ํ•™์ƒ ๋ฉ”๋‰ด์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Utility. Industries: Academic. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 4608 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

ํ•™์ƒ ๋ฉ”๋‰ด

ํ•ต์‹ฌ ํ†ต๊ณ„ ๊ฐœ๋…์„ ๊ต์œกํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๋Œ€ํ™”์‹ ์• ํ”Œ๋ฆฟ์ด ํฌํ•จ๋œ ํ•™์ƒ ๋ฉ”๋‰ด์ž…๋‹ˆ๋‹ค

์œ ํ‹ธ๋ฆฌํ‹ฐ

4.6k ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

๋Ÿฐ๋ด‡. ์‚ฌ์šฉ์ž๊ฐ€ JMPยฎ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๋” ํšจ๊ณผ์ ์œผ๋กœ ํƒ์ƒ‰ํ•˜๊ณ  ์‚ฌ์šฉํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋Š” ๋ด‡์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Utility, Documentation. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 4.54 / 5. 2912 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

๋Ÿฐ๋ด‡

์‚ฌ์šฉ์ž๊ฐ€ JMPยฎ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๋” ํšจ๊ณผ์ ์œผ๋กœ ํƒ์ƒ‰ํ•˜๊ณ  ์‚ฌ์šฉํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋Š” ๋ด‡์ž…๋‹ˆ๋‹ค

์„ค๋ช…์„œ, ์œ ํ‹ธ๋ฆฌํ‹ฐ

2.9k ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

๊ณต์ • ๋Šฅ๋ ฅ ํƒ์ƒ‰๊ธฐ. ํ”„๋กœ์„ธ์Šค ์—ญ๋Ÿ‰์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•œ ์ƒํ˜ธ ์ž‘์šฉ์ ์ด๊ณ  ๊ฐ„์†Œํ™”๋œ ์ ‘๊ทผ ๋ฐฉ์‹์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Visualization. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 1305 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

๊ณต์ • ๋Šฅ๋ ฅ ํƒ์ƒ‰๊ธฐ

ํ”„๋กœ์„ธ์Šค ์—ญ๋Ÿ‰์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•œ ์ƒํ˜ธ ์ž‘์šฉ์ ์ด๊ณ  ๊ฐ„์†Œํ™”๋œ ์ ‘๊ทผ ๋ฐฉ์‹์ž…๋‹ˆ๋‹ค

๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

1.3k ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

JMPยฎ Pro์šฉ Torch Deep Learning. ์‹ฌ์ธต ์‹ ๊ฒฝ๋ง์„ ์‚ฌ์šฉํ•œ ์˜ˆ์ธก ๋ชจ๋ธ๋ง์„ ์œ„ํ•ด ๋งŽ์ด ์‚ฌ์šฉ๋˜๋Š” PyTorch ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ์— ๋Œ€ํ•œ ์ฝ”๋“œ ์—†๋Š” ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Machine Learning. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 4.83 / 5. 1138 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

JMPยฎ Pro์šฉ Torch Deep Learning

์‹ฌ์ธต ์‹ ๊ฒฝ๋ง์„ ์‚ฌ์šฉํ•œ ์˜ˆ์ธก ๋ชจ๋ธ๋ง์„ ์œ„ํ•ด ๋งŽ์ด ์‚ฌ์šฉ๋˜๋Š” PyTorch ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ์— ๋Œ€ํ•œ ์ฝ”๋“œ ์—†๋Š” ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค.

๋จธ์‹  ๋Ÿฌ๋‹

1.1k ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

ํ˜„๋Œ€ ์‹์Šค ์‹œ๊ทธ๋งˆ. JMPยฎ ๋‚ด์—์„œ Six Sigma DMAIC(์ •์˜, ์ธก์ •, ๋ถ„์„, ๊ฐœ์„ , ์ œ์–ด) ํ”„๋กœ์„ธ์Šค๋ฅผ ๊ฐ„์†Œํ™”ํ•˜๊ธฐ ์œ„ํ•œ ๋„๊ตฌ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Six Sigma. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 4 / 5. 897 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

ํ˜„๋Œ€ ์‹์Šค ์‹œ๊ทธ๋งˆ

JMPยฎ ๋‚ด์—์„œ Six Sigma DMAIC(์ •์˜, ์ธก์ •, ๋ถ„์„, ๊ฐœ์„ , ์ œ์–ด) ํ”„๋กœ์„ธ์Šค๋ฅผ ๊ฐ„์†Œํ™”ํ•˜๊ธฐ ์œ„ํ•œ ๋„๊ตฌ์ž…๋‹ˆ๋‹ค

Six Sigma

897 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

๋ฐ์ดํ„ฐ ๋ถ„์„ ๋””๋ ‰ํ„ฐ. JMPยฎ์—์„œ ๋‹ค์–‘ํ•œ ๋ถ„์„์„ ์‚ฌ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์„ค๋ช…ํ•˜๋Š” ์ƒˆ๋กœ์šด ์‚ฌ์šฉ์ž๋ฅผ ์œ„ํ•œ ๊ฐ€์ด๋“œ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Analysis, Documentation, Six Sigma. Industries: Academic. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 864 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

๋ฐ์ดํ„ฐ ๋ถ„์„ ๋””๋ ‰ํ„ฐ

JMPยฎ์—์„œ ๋‹ค์–‘ํ•œ ๋ถ„์„์„ ์‚ฌ์šฉํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์„ค๋ช…ํ•˜๋Š” ์ƒˆ๋กœ์šด ์‚ฌ์šฉ์ž๋ฅผ ์œ„ํ•œ ๊ฐ€์ด๋“œ์ž…๋‹ˆ๋‹ค

Six Sigma, ๋ฐ์ดํ„ฐ ๋ถ„์„, ์„ค๋ช…์„œ

864 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

JMPยฎ Pro์šฉ XGBoost. ์˜ˆ์ธก ๋ชจ๋ธ๋ง์„ ์œ„ํ•œ ์ธ๊ธฐ ์˜คํ”ˆ ์†Œ์Šค ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ XGBoost์˜ ํฌ์ธํŠธ ์•ค ํด๋ฆญ ์ธํ„ฐํŽ˜์ด์Šค. ๋ฒ”์ฃผ: Machine Learning, Data Science. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 802 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

JMPยฎ Pro์šฉ XGBoost

์˜ˆ์ธก ๋ชจ๋ธ๋ง์„ ์œ„ํ•œ ์ธ๊ธฐ ์˜คํ”ˆ ์†Œ์Šค ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ XGBoost์˜ ํฌ์ธํŠธ ์•ค ํด๋ฆญ ์ธํ„ฐํŽ˜์ด์Šค

๋ฐ์ดํ„ฐ ๊ณผํ•™, ๋จธ์‹  ๋Ÿฌ๋‹

802 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

๊ทธ๋ž˜ํ”„ ๋นŒ๋” ๋„๊ตฌ ๋ชจ์Œ. ๊ทธ๋ž˜ํ”„ ๋นŒ๋” ๋ฐ ๊ธฐํƒ€ ๋ณด๊ณ ์„œ์— ์œ ์šฉํ•œ ๋„์›€๋ง ํ•จ์ˆ˜๊ฐ€ ํฌํ•จ๋œ ๋„๊ตฌ ์ƒ์ž. ๋ฒ”์ฃผ: Data Visualization. ํ‰์ : 5 / 5. 657 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

๊ทธ๋ž˜ํ”„ ๋นŒ๋” ๋„๊ตฌ ๋ชจ์Œ

๊ทธ๋ž˜ํ”„ ๋นŒ๋” ๋ฐ ๊ธฐํƒ€ ๋ณด๊ณ ์„œ์— ์œ ์šฉํ•œ ๋„์›€๋ง ํ•จ์ˆ˜๊ฐ€ ํฌํ•จ๋œ ๋„๊ตฌ ์ƒ์ž

๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

657 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์‹คํ—˜์ž์— ๋Œ€ํ•œ ๊ทธ๋ž˜ํ”„. ํ…œํ”Œ๋ฆฟ ํ…Œ์ด๋ธ”์„ ์Œ“์ธ ๋ฐ์ดํ„ฐ ํ˜•์‹์œผ๋กœ ๋ณ€ํ™˜ํ•œ ์ƒ˜ํ”Œ ๋ฐ์ดํ„ฐ์˜ ๊ณตํ†ต ๊ทธ๋ž˜ํ”„ ๋ฐ ๊ด€๋ จ ๋ถ„์„. ๋ฒ”์ฃผ: Data Analysis, Data Visualization. JMP์—์„œ ์ œ์ž‘. 621 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์‹คํ—˜์ž์— ๋Œ€ํ•œ ๊ทธ๋ž˜ํ”„

ํ…œํ”Œ๋ฆฟ ํ…Œ์ด๋ธ”์„ ์Œ“์ธ ๋ฐ์ดํ„ฐ ํ˜•์‹์œผ๋กœ ๋ณ€ํ™˜ํ•œ ์ƒ˜ํ”Œ ๋ฐ์ดํ„ฐ์˜ ๊ณตํ†ต ๊ทธ๋ž˜ํ”„ ๋ฐ ๊ด€๋ จ ๋ถ„์„

๋ฐ์ดํ„ฐ ๋ถ„์„, ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

621 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ผ๋ณธ์–ด ์„ค๋ช…์„œ. ๋ชจ๋“  JMP ์„ค๋ช…์„œ ๋ฐ ์„ค๋ช…์„œ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ์šฉ PDF ํŒŒ์ผ. ๋ฒ”์ฃผ: Documentation. JMP์—์„œ ์ œ์ž‘. 617 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์ผ๋ณธ์–ด ์„ค๋ช…์„œ

๋ชจ๋“  JMP ์„ค๋ช…์„œ ๋ฐ ์„ค๋ช…์„œ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ์šฉ PDF ํŒŒ์ผ

์„ค๋ช…์„œ

617 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

ํฌ๋ ˆ์ŠคํŠธ ๊ทธ๋ฆผ. ๊ทธ๋ž˜ํ”„ ๋นŒ๋”๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํฌ๋ ˆ์ŠคํŠธ ํ”Œ๋กฏ์„ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ๋„๊ตฌ. ๋ฒ”์ฃผ: Data Visualization. JMP์—์„œ ์ œ์ž‘. 607 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

ํฌ๋ ˆ์ŠคํŠธ ๊ทธ๋ฆผ

๊ทธ๋ž˜ํ”„ ๋นŒ๋”๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํฌ๋ ˆ์ŠคํŠธ ํ”Œ๋กฏ์„ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ๋„๊ตฌ

๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

607 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์˜์–ด ์„ค๋ช…์„œ. ๋ชจ๋“  JMP ์„ค๋ช…์„œ ๋ฐ ์„ค๋ช…์„œ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ์šฉ PDF ํŒŒ์ผ. ๋ฒ”์ฃผ: Documentation. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 556 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์˜์–ด ์„ค๋ช…์„œ

๋ชจ๋“  JMP ์„ค๋ช…์„œ ๋ฐ ์„ค๋ช…์„œ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ์šฉ PDF ํŒŒ์ผ

์„ค๋ช…์„œ

556 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ตœ๊ณ  ํ‰์ 

์„ ๋ฒ„์ŠคํŠธ ํ”Œ๋กฏ. ๋‚ดํฌ ํŒŒ์ด ์ฐจํŠธ์˜ ์„ ๋ฒ„์ŠคํŠธ ์Šคํƒ€์ผ ๊ทธ๋ฆผ์—์„œ ๊ณ„์ธต์  ๋ฐ์ดํ„ฐ์˜ ๋น„๋ก€ ๋ถ€๋ถ„์„ ๋ณด์—ฌ ์ฃผ๋Š” ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๋„๊ตฌ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Visualization. Industries: Consumer Products. ํ‰์ : 5 / 5. 48 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์„ ๋ฒ„์ŠคํŠธ ํ”Œ๋กฏ

๋‚ดํฌ ํŒŒ์ด ์ฐจํŠธ์˜ ์„ ๋ฒ„์ŠคํŠธ ์Šคํƒ€์ผ ๊ทธ๋ฆผ์—์„œ ๊ณ„์ธต์  ๋ฐ์ดํ„ฐ์˜ ๋น„๋ก€ ๋ถ€๋ถ„์„ ๋ณด์—ฌ ์ฃผ๋Š” ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๋„๊ตฌ์ž…๋‹ˆ๋‹ค.

๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

48 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

ํ…Œ์ด๋ธ” ์ƒ์„ฑ-RTF ํ…Œ์ด๋ธ”. ์ง€์ •๋œ JMP Tabulate์˜ 3ํ–‰ RTF ํŒŒ์ผ์„ ์ƒ์„ฑ. ๋ฒ”์ฃผ: Data Analysis, Data Visualization. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 26 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

ํ…Œ์ด๋ธ” ์ƒ์„ฑ-RTF ํ…Œ์ด๋ธ”

์ง€์ •๋œ JMP Tabulate์˜ 3ํ–‰ RTF ํŒŒ์ผ์„ ์ƒ์„ฑ

๋ฐ์ดํ„ฐ ๋ถ„์„, ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

26 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ค‘๊ตญ์–ด ์„ค๋ช…์„œ. ๋ชจ๋“  JMP ์„ค๋ช…์„œ ๋ฐ ์„ค๋ช…์„œ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ์šฉ PDF ํŒŒ์ผ. ๋ฒ”์ฃผ: Documentation. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 398 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์ค‘๊ตญ์–ด ์„ค๋ช…์„œ

๋ชจ๋“  JMP ์„ค๋ช…์„œ ๋ฐ ์„ค๋ช…์„œ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ์šฉ PDF ํŒŒ์ผ

์„ค๋ช…์„œ

398 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

๋ฒค ๋‹ค์ด์–ด๊ทธ๋žจ. JMPยฎ๋กœ ๋ฒค ๋‹ค์ด์–ด๊ทธ๋žจ์„ ์ƒ์„ฑํ•˜๋Š” ๋„๊ตฌ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Visualization. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 528 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

๋ฒค ๋‹ค์ด์–ด๊ทธ๋žจ

JMPยฎ๋กœ ๋ฒค ๋‹ค์ด์–ด๊ทธ๋žจ์„ ์ƒ์„ฑํ•˜๋Š” ๋„๊ตฌ์ž…๋‹ˆ๋‹ค

๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

528 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

JMPยฎ Pro์šฉ XGBoost. ์˜ˆ์ธก ๋ชจ๋ธ๋ง์„ ์œ„ํ•œ ์ธ๊ธฐ ์˜คํ”ˆ ์†Œ์Šค ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ XGBoost์˜ ํฌ์ธํŠธ ์•ค ํด๋ฆญ ์ธํ„ฐํŽ˜์ด์Šค. ๋ฒ”์ฃผ: Data Science, Machine Learning. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 802 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

JMPยฎ Pro์šฉ XGBoost

์˜ˆ์ธก ๋ชจ๋ธ๋ง์„ ์œ„ํ•œ ์ธ๊ธฐ ์˜คํ”ˆ ์†Œ์Šค ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ XGBoost์˜ ํฌ์ธํŠธ ์•ค ํด๋ฆญ ์ธํ„ฐํŽ˜์ด์Šค

๋ฐ์ดํ„ฐ ๊ณผํ•™, ๋จธ์‹  ๋Ÿฌ๋‹

802 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

OFAT ๋Œ€ DOE ์‹œ์—ฐ. OFAT ์‹คํ—˜ ๊ฒฐ๊ณผ์™€ DOE ๋ฐฉ๋ฒ•์„ ๋Œ€์กฐํ•˜๋Š” ๊ฐ„๋‹จํ•œ ๋Œ€์‹œ๋ณด๋“œ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Experimental Design. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 309 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

OFAT ๋Œ€ DOE ์‹œ์—ฐ

OFAT ์‹คํ—˜ ๊ฒฐ๊ณผ์™€ DOE ๋ฐฉ๋ฒ•์„ ๋Œ€์กฐํ•˜๋Š” ๊ฐ„๋‹จํ•œ ๋Œ€์‹œ๋ณด๋“œ์ž…๋‹ˆ๋‹ค

์‹คํ—˜ ์„ค๊ณ„

309 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

JMPยฎ Pro ์šฉ Torch Companion. Torch Deep Learning ์ถ”๊ฐ€ ๊ธฐ๋Šฅ์˜ ์ดˆ๋ชจ์ˆ˜๋ฅผ ์ž๋™์œผ๋กœ ์„ ๋ณ„ํ•˜๋Š” ๋„๊ตฌ. ๋ฒ”์ฃผ: Data Analysis, Machine Learning, Experimental Design. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 184 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

JMPยฎ Pro ์šฉ Torch Companion

Torch Deep Learning ์ถ”๊ฐ€ ๊ธฐ๋Šฅ์˜ ์ดˆ๋ชจ์ˆ˜๋ฅผ ์ž๋™์œผ๋กœ ์„ ๋ณ„ํ•˜๋Š” ๋„๊ตฌ

๋ฐ์ดํ„ฐ ๋ถ„์„, ๋จธ์‹  ๋Ÿฌ๋‹, ์‹คํ—˜ ์„ค๊ณ„

184 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

3D๋กœ ์œ ์ • ํŠธ๋ ˆ์ด์Šค ๊ทธ๋ฆผ. ๋ฐฉํ–ฅ ์ธก๋Ÿ‰ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•œ 3D ์œ ์ • ๊ถค์  ๋„์‹œ ๋ฐฉ๋ฒ•. ๋ฒ”์ฃผ: Data Visualization. Industries: Clean Energy & Conservation. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 69 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

3D๋กœ ์œ ์ • ํŠธ๋ ˆ์ด์Šค ๊ทธ๋ฆผ

๋ฐฉํ–ฅ ์ธก๋Ÿ‰ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•œ 3D ์œ ์ • ๊ถค์  ๋„์‹œ ๋ฐฉ๋ฒ•

๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

69 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ถ”๊ฐ€๊ธฐ๋Šฅ ๊ด€๋ฆฌ์ž. ์ถ”๊ฐ€๊ธฐ๋Šฅ ํŒŒ์ผ์„ ์‰ฝ๊ฒŒ ๋นŒ๋“œ ๋ฐ ์‚ฌ์šฉ์ž ์ •์˜ํ•˜๊ณ , ์ถ”๊ฐ€๊ธฐ๋Šฅ ๋ฒ„์ „์„ ๊ด€๋ฆฌํ•˜๊ณ , ์†Œ์Šค ํŒŒ์ผ์— ์•ก์„ธ์Šคํ•˜๊ธฐ ์œ„ํ•œ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Utility. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 506 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์ถ”๊ฐ€๊ธฐ๋Šฅ ๊ด€๋ฆฌ์ž

์ถ”๊ฐ€๊ธฐ๋Šฅ ํŒŒ์ผ์„ ์‰ฝ๊ฒŒ ๋นŒ๋“œ ๋ฐ ์‚ฌ์šฉ์ž ์ •์˜ํ•˜๊ณ , ์ถ”๊ฐ€๊ธฐ๋Šฅ ๋ฒ„์ „์„ ๊ด€๋ฆฌํ•˜๊ณ , ์†Œ์Šค ํŒŒ์ผ์— ์•ก์„ธ์Šคํ•˜๊ธฐ ์œ„ํ•œ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค

์œ ํ‹ธ๋ฆฌํ‹ฐ

506 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

ํ•™์ƒ ๋ฉ”๋‰ด. ํ•ต์‹ฌ ํ†ต๊ณ„ ๊ฐœ๋…์„ ๊ต์œกํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๋Œ€ํ™”์‹ ์• ํ”Œ๋ฆฟ์ด ํฌํ•จ๋œ ํ•™์ƒ ๋ฉ”๋‰ด์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Utility. Industries: Academic. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 4608 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

ํ•™์ƒ ๋ฉ”๋‰ด

ํ•ต์‹ฌ ํ†ต๊ณ„ ๊ฐœ๋…์„ ๊ต์œกํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๋Œ€ํ™”์‹ ์• ํ”Œ๋ฆฟ์ด ํฌํ•จ๋œ ํ•™์ƒ ๋ฉ”๋‰ด์ž…๋‹ˆ๋‹ค

์œ ํ‹ธ๋ฆฌํ‹ฐ

4.6k ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

OneDrive ๋ฐSharePoint ๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ. Microsoft OneDrive ๋ฐ SharePoint ๋ชฉ๋ก์˜ ๋ฐ์ดํ„ฐ ๊ฐ€์ ธ์˜ค๊ธฐ ๋ฐ ์ฟผ๋ฆฌ. ๋ฒ”์ฃผ: Data Connectors. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 228 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

OneDrive ๋ฐSharePoint ๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ

Microsoft OneDrive ๋ฐ SharePoint ๋ชฉ๋ก์˜ ๋ฐ์ดํ„ฐ ๊ฐ€์ ธ์˜ค๊ธฐ ๋ฐ ์ฟผ๋ฆฌ

๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ

228 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

JMPยฎ Pro๋ฅผ ์œ„ํ•œ ์‹ ๊ฒฝ๋ง ์กฐ์ •. ์€๋‹‰์ธต, ๋ถ€์ŠคํŠธ ๋ฐ ์ ํ•ฉ ์˜ต์…˜์— ๋Œ€ํ•œ ์ตœ์  ๋ชจ์ˆ˜๋ฅผ ์ฐพ๊ธฐ ์œ„ํ•ด ๋‹ค์ค‘ ์‹ ๊ฒฝ๋ง์„ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Science. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 405 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

JMPยฎ Pro๋ฅผ ์œ„ํ•œ ์‹ ๊ฒฝ๋ง ์กฐ์ •

์€๋‹‰์ธต, ๋ถ€์ŠคํŠธ ๋ฐ ์ ํ•ฉ ์˜ต์…˜์— ๋Œ€ํ•œ ์ตœ์  ๋ชจ์ˆ˜๋ฅผ ์ฐพ๊ธฐ ์œ„ํ•ด ๋‹ค์ค‘ ์‹ ๊ฒฝ๋ง์„ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค

๋ฐ์ดํ„ฐ ๊ณผํ•™

405 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ตœ๊ทผ ๊ฒŒ์‹œ

ํ”„๋ ˆ์  ํ…Œ์ด์…˜ ๋„๊ตฌ. JMP ์—์„œ ์ฒญ์ค‘ ์•ž์—์„œ ํ”„๋ ˆ์  ํ…Œ์ด์…˜ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋Š” ๋„๊ตฌ ๋ชจ์Œ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Utility. JMP์—์„œ ์ œ์ž‘. 12 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

ํ”„๋ ˆ์  ํ…Œ์ด์…˜ ๋„๊ตฌ

JMP ์—์„œ ์ฒญ์ค‘ ์•ž์—์„œ ํ”„๋ ˆ์  ํ…Œ์ด์…˜ํ•˜๋Š” ๋ฐ ๋„์›€์ด ๋˜๋Š” ๋„๊ตฌ ๋ชจ์Œ์ž…๋‹ˆ๋‹ค

์œ ํ‹ธ๋ฆฌํ‹ฐ

12 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

๊ฐ€์† ์•ˆ์ •์„ฑ. ๊ฐ€์† ์•ˆ์ •์„ฑ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด ์ „๋ฌธ ๋ชจํ˜•์„ ์ž๋™์œผ๋กœ ์ ํ•ฉ, ์„ ํƒ ๋ฐ ํƒ์ƒ‰ํ•˜๋Š” ๋„๊ตฌ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Analysis. Industries: Pharmaceuticals. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 61 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

๊ฐ€์† ์•ˆ์ •์„ฑ

๊ฐ€์† ์•ˆ์ •์„ฑ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•ด ์ „๋ฌธ ๋ชจํ˜•์„ ์ž๋™์œผ๋กœ ์ ํ•ฉ, ์„ ํƒ ๋ฐ ํƒ์ƒ‰ํ•˜๋Š” ๋„๊ตฌ์ž…๋‹ˆ๋‹ค.

๋ฐ์ดํ„ฐ ๋ถ„์„

61 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ƒ์กด ํƒ์ƒ‰๊ธฐ. ์œ„ํ—˜ ํ™˜์ž ์ˆ˜ ํ…Œ์ด๋ธ”์ด ํฌํ•จ๋œ ๋™์ ์œผ๋กœ ์—…๋ฐ์ดํŠธ๋˜๋Š” Kaplan-Meier ํ”Œ๋กฏ์„ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Analysis, Data Visualization. JMP์—์„œ ์ œ์ž‘. 26 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์ƒ์กด ํƒ์ƒ‰๊ธฐ

์œ„ํ—˜ ํ™˜์ž ์ˆ˜ ํ…Œ์ด๋ธ”์ด ํฌํ•จ๋œ ๋™์ ์œผ๋กœ ์—…๋ฐ์ดํŠธ๋˜๋Š” Kaplan-Meier ํ”Œ๋กฏ์„ ์ƒ์„ฑํ•˜๊ธฐ ์œ„ํ•œ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค

๋ฐ์ดํ„ฐ ๋ถ„์„, ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

26 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ถ”๊ฐ€ ๊ธฐ๋Šฅ ์Šคํƒ€ํ„ฐ ํ‚คํŠธ. ์ถ”๊ฐ€๊ธฐ๋Šฅ ๊ฐœ๋ฐœ์˜ ๊ธฐ๋ณธ ์‚ฌํ•ญ์„ ํ•™์Šตํ•˜๊ธฐ ์œ„ํ•œ ๊ฐ€์ด๋“œ. ๋ฒ”์ฃผ: Utility. JMP์—์„œ ์ œ์ž‘. 26 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์ถ”๊ฐ€ ๊ธฐ๋Šฅ ์Šคํƒ€ํ„ฐ ํ‚คํŠธ

์ถ”๊ฐ€๊ธฐ๋Šฅ ๊ฐœ๋ฐœ์˜ ๊ธฐ๋ณธ ์‚ฌํ•ญ์„ ํ•™์Šตํ•˜๊ธฐ ์œ„ํ•œ ๊ฐ€์ด๋“œ

์œ ํ‹ธ๋ฆฌํ‹ฐ

26 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

๋ฐ˜๋„์ฒด ํˆดํ‚คํŠธ. ๋ฐ˜๋„์ฒด ์‚ฐ์—…์˜ ํŠน์ˆ˜ํ•œ ์‹œ๊ฐํ™” ๋ฐ ๋ถ„์„ ๋ฌธ์ œ๋ฅผ ์œ„ํ•ด ์„ค๊ณ„๋œ ๋„๊ตฌ ๋ชจ์Œ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Analysis, Data Visualization, Utility. Industries: Semiconductor. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 5 / 5. 134 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

๋ฐ˜๋„์ฒด ํˆดํ‚คํŠธ

๋ฐ˜๋„์ฒด ์‚ฐ์—…์˜ ํŠน์ˆ˜ํ•œ ์‹œ๊ฐํ™” ๋ฐ ๋ถ„์„ ๋ฌธ์ œ๋ฅผ ์œ„ํ•ด ์„ค๊ณ„๋œ ๋„๊ตฌ ๋ชจ์Œ์ž…๋‹ˆ๋‹ค.

๋ฐ์ดํ„ฐ ๋ถ„์„, ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”, ์œ ํ‹ธ๋ฆฌํ‹ฐ

134 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์„ ๋ฒ„์ŠคํŠธ ํ”Œ๋กฏ. ๋‚ดํฌ ํŒŒ์ด ์ฐจํŠธ์˜ ์„ ๋ฒ„์ŠคํŠธ ์Šคํƒ€์ผ ๊ทธ๋ฆผ์—์„œ ๊ณ„์ธต์  ๋ฐ์ดํ„ฐ์˜ ๋น„๋ก€ ๋ถ€๋ถ„์„ ๋ณด์—ฌ ์ฃผ๋Š” ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๋„๊ตฌ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Visualization. Industries: Consumer Products. ํ‰์ : 5 / 5. 48 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์„ ๋ฒ„์ŠคํŠธ ํ”Œ๋กฏ

๋‚ดํฌ ํŒŒ์ด ์ฐจํŠธ์˜ ์„ ๋ฒ„์ŠคํŠธ ์Šคํƒ€์ผ ๊ทธ๋ฆผ์—์„œ ๊ณ„์ธต์  ๋ฐ์ดํ„ฐ์˜ ๋น„๋ก€ ๋ถ€๋ถ„์„ ๋ณด์—ฌ ์ฃผ๋Š” ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™” ๋„๊ตฌ์ž…๋‹ˆ๋‹ค.

๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

48 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

Albert Invent, JMP ์ปค๋„ฅํ„ฐ ๊ฐœ๋ฐœ. ์•Œ๋ฒ ๋ฅดํŠธ Albert Invent๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ ๋ฐ ์ €์žฅํ•˜๋Š” ๊ฒฝ์šฐ ๋ถ„์„ ๋ฐ ์‹œ๊ฐํ™”๋ฅผ ์œ„ํ•ด ๋ฐ์ดํ„ฐ๋ฅผ JMP ๋กœ ์ง์ ‘ ๊ฐ€์ ธ์™€์•ผ ํ•ฉ๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Connectors. Industries: Chemical. 21 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

Albert Invent, JMP ์ปค๋„ฅํ„ฐ ๊ฐœ๋ฐœ

์•Œ๋ฒ ๋ฅดํŠธ Albert Invent๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋ฐ์ดํ„ฐ๋ฅผ ์ˆ˜์ง‘ ๋ฐ ์ €์žฅํ•˜๋Š” ๊ฒฝ์šฐ ๋ถ„์„ ๋ฐ ์‹œ๊ฐํ™”๋ฅผ ์œ„ํ•ด ๋ฐ์ดํ„ฐ๋ฅผ JMP ๋กœ ์ง์ ‘ ๊ฐ€์ ธ์™€์•ผ ํ•ฉ๋‹ˆ๋‹ค.

๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ

21 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์ˆœ์ฐจ ํ‘œ์ง‘ ๋ฐ OC ๊ณก์„  ๊ณ„์‚ฐ๊ธฐ. ์ž…๋ ฅ ๋˜๋Š” ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•œ ์ˆœ์ฐจ ํ‘œ์ง‘ ๋˜๋Š” ๋‹จ์ผ ํ‘œ๋ณธ OC ๊ณก์„ ์„ ๊ณ„์‚ฐํ•˜๊ธฐ ์œ„ํ•œ ๊ณ„์‚ฐ๊ธฐ์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Data Analysis, Data Visualization, Six Sigma. JMP์—์„œ ์ œ์ž‘. 25 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์ˆœ์ฐจ ํ‘œ์ง‘ ๋ฐ OC ๊ณก์„  ๊ณ„์‚ฐ๊ธฐ

์ž…๋ ฅ ๋˜๋Š” ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ฐ์ดํ„ฐ๋ฅผ ์‚ฌ์šฉํ•œ ์ˆœ์ฐจ ํ‘œ์ง‘ ๋˜๋Š” ๋‹จ์ผ ํ‘œ๋ณธ OC ๊ณก์„ ์„ ๊ณ„์‚ฐํ•˜๊ธฐ ์œ„ํ•œ ๊ณ„์‚ฐ๊ธฐ์ž…๋‹ˆ๋‹ค.

Six Sigma, ๋ฐ์ดํ„ฐ ๋ถ„์„, ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”

25 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์–ด์‹œ์Šคํ„ดํŠธ. ์ผ๋ฐ˜์ ์œผ๋กœ ์‚ฌ์šฉ๋˜๋Š” LLM์„ ์‚ฌ์šฉํ•˜์—ฌ ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด JSL ์ž‘์„ฑ, ๋ถ„์„ ์‹คํ–‰, ๋ฐ์ดํ„ฐ ํƒ์ƒ‰ ๋“ฑ์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ•๋ ฅํ•˜๊ณ  ์œ ์—ฐํ•œ JMP ์šฉ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Machine Learning, Utility. JMP์—์„œ ์ œ์ž‘. ํ‰์ : 3 / 5. 553 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์–ด์‹œ์Šคํ„ดํŠธ

์ผ๋ฐ˜์ ์œผ๋กœ ์‚ฌ์šฉ๋˜๋Š” LLM์„ ์‚ฌ์šฉํ•˜์—ฌ ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด JSL ์ž‘์„ฑ, ๋ถ„์„ ์‹คํ–‰, ๋ฐ์ดํ„ฐ ํƒ์ƒ‰ ๋“ฑ์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ•๋ ฅํ•˜๊ณ  ์œ ์—ฐํ•œ JMP ์šฉ ์ธํ„ฐํŽ˜์ด์Šค์ž…๋‹ˆ๋‹ค.

๋จธ์‹  ๋Ÿฌ๋‹, ์œ ํ‹ธ๋ฆฌํ‹ฐ

553 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

ํ…Œ์ด๋ธ” ์ƒ์„ฑ-DOCX ํ…Œ์ด๋ธ”. ๋ฐ์ดํ„ฐ ํ…Œ์ด๋ธ” ๋ฐ Tabulate ํ”Œ๋žซํผ ๊ฒฐ๊ณผ๋กœ๋ถ€ํ„ฐ DOCX ํ˜•์‹์˜ ํ…Œ์ด๋ธ”์„ ๋งŒ๋“œ๋Š” ๋„๊ตฌ. ๋ฒ”์ฃผ: Utility, Documentation. JMP์—์„œ ์ œ์ž‘. 33 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

ํ…Œ์ด๋ธ” ์ƒ์„ฑ-DOCX ํ…Œ์ด๋ธ”

๋ฐ์ดํ„ฐ ํ…Œ์ด๋ธ” ๋ฐ Tabulate ํ”Œ๋žซํผ ๊ฒฐ๊ณผ๋กœ๋ถ€ํ„ฐ DOCX ํ˜•์‹์˜ ํ…Œ์ด๋ธ”์„ ๋งŒ๋“œ๋Š” ๋„๊ตฌ

์„ค๋ช…์„œ, ์œ ํ‹ธ๋ฆฌํ‹ฐ

33 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

์™„ํ™”๋œ Elastic Net๊ณผ R์„ ์‚ฌ์šฉํ•œ Lasso ํšŒ๊ท€ SVEM. Elastic Net ๋˜๋Š” Lasso SVEM ๋ชจํ˜•์„ ํ…Œ์ด๋ธ” ์Šคํฌ๋ฆฝํŠธ์— ์ €์žฅ๋œ ๋ชจํ˜• ์ ํ•ฉ ๊ฐœ์ฒด์— ์ ํ•ฉ์‹œํ‚ต๋‹ˆ๋‹ค. ์ „์ฒด ๋ชจํ˜• ๊ฒ€์ •๋„ ์‹คํ–‰ํ•ฉ๋‹ˆ๋‹ค. ๋ฒ”์ฃผ: Machine Learning, Data Analysis, Statistical Modeling. ํ‰์ : 5 / 5. 18 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

์™„ํ™”๋œ Elastic Net๊ณผ R์„ ์‚ฌ์šฉํ•œ Lasso ํšŒ๊ท€ SVEM

Elastic Net ๋˜๋Š” Lasso SVEM ๋ชจํ˜•์„ ํ…Œ์ด๋ธ” ์Šคํฌ๋ฆฝํŠธ์— ์ €์žฅ๋œ ๋ชจํ˜• ์ ํ•ฉ ๊ฐœ์ฒด์— ์ ํ•ฉ์‹œํ‚ต๋‹ˆ๋‹ค. ์ „์ฒด ๋ชจํ˜• ๊ฒ€์ •๋„ ์‹คํ–‰ํ•ฉ๋‹ˆ๋‹ค.

๋ฐ์ดํ„ฐ ๋ถ„์„, ๋จธ์‹  ๋Ÿฌ๋‹, ํ†ต๊ณ„ ๋ชจ๋ธ๋ง

18 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

MongoDB ๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ. MongoDB์—์„œ ๋ฐ์ดํ„ฐ ๊ฐ€์ ธ์˜ค๊ธฐ ๋ฐ ์ฟผ๋ฆฌ. ๋ฒ”์ฃผ: Data Connectors. JMP์—์„œ ์ œ์ž‘. 12 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜.

MongoDB ๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ

MongoDB์—์„œ ๋ฐ์ดํ„ฐ ๊ฐ€์ ธ์˜ค๊ธฐ ๋ฐ ์ฟผ๋ฆฌ

๋ฐ์ดํ„ฐ ์ปค๋„ฅํ„ฐ

12 ๋‹ค์šด๋กœ๋“œ ํšŸ์ˆ˜

JMP๋ฅผ ์ฒ˜์Œ ์‚ฌ์šฉํ•˜์‹œ๋‚˜์š”? ๋ฌด๋ฃŒ ํ‰๊ฐ€ํŒ ๋‹ค์šด๋กœ๋“œ