๋ณธ๋ฌธ ๋ฐ”๋กœ๊ฐ€๊ธฐ

Study๐Ÿ“š/AI&SW

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Jupyter Notebook(์ฃผํ”ผํ„ฐ ๋…ธํŠธ๋ถ)์˜ ํŠน์ง•๊ณผ ์‚ฌ์šฉ๋ฒ• Jupyter Notebook(์ฃผํ”ผํ„ฐ ๋…ธํŠธ๋ถ)์€ ๋ฐ์ดํ„ฐ ๋ถ„์„, ๋จธ์‹ ๋Ÿฌ๋‹, ๊ณผํ•™ ๊ณ„์‚ฐ ๊ฐ™์€ ์ž‘์—…์—์„œ ๋งŽ์ด ์‚ฌ์šฉ๋˜๋Š” ๊ฐœ๋ฐœ ๋„๊ตฌ๋‹ค. ์ฃผํ”ผํ„ฐ๋Š” ํŒŒ์ด์ฌ ๊ธฐ๋ฐ˜ ๋จธ์‹ ๋Ÿฌ๋‹ ์ž‘์—…์—์„œ ์‚ฌ์‹ค์ƒ ํ‘œ์ค€ ๋„๊ตฌ๋กœ ์ž๋ฆฌ ์žก๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ๋ฐ์ดํ„ฐ ๋ถ„์„, ๋ชจ๋ธ ๊ฐœ๋ฐœ, ์‹œ๊ฐํ™” ๋“ฑ ์ „๋ฐ˜์ ์ธ ์›Œํฌํ”Œ๋กœ๋ฅผ ์ฒ˜๋ฆฌํ•˜๋Š” ๋ฐ ์ ํ•ฉํ•˜๋‹ค.  ์ฃผ์š” ํŠน์ง• ์ฝ”๋“œ์™€ ๊ฒฐ๊ณผ๋ฅผ ํ•จ๊ป˜ ํ‘œ์‹œํ•  ์ˆ˜ ์žˆ์Œ์ฝ”๋“œ๋ฅผ ์ž‘์„ฑํ•˜๊ณ  ์‹คํ–‰ํ•˜๋ฉด, ๊ฒฐ๊ณผ๊ฐ€ ๋ฐ”๋กœ ์•„๋ž˜์— ํ‘œ์‹œ๋œ๋‹ค. ๋ฐ์ดํ„ฐ๋ฅผ ๋ฐ”๋กœ ์‹คํ–‰, ์ˆ˜์ •, ๋‹ค์‹œ ์‹คํ–‰ํ•  ์ˆ˜ ์žˆ์–ด ์ž‘์—… ํ๋ฆ„์ด ์œ ์—ฐํ•˜๋‹ค. ๋‹ค์–‘ํ•œ ์–ธ์–ด ์ง€์› ์ด๋ฆ„ Jupyter ์ž์ฒด๊ฐ€ Julia, Python, R์—์„œ ์œ ๋ž˜๋œ ์ด๋ฆ„์ด๋‹ค. ์ฃผ๋กœ Python์„ ์‚ฌ์šฉํ•˜์ง€๋งŒ, R, Julia, C++ ๋“ฑ๋„ ์ง€์›ํ•œ๋‹ค.   ๋งˆํฌ๋‹ค์šด(Markdown) ๊ฐ€๋Šฅ์ฝ”๋“œ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ์„ค๋ช…, ์ˆ˜์‹, ์ด๋ฏธ์ง€ ๋“ฑ์„..
๋จธ์‹ ๋Ÿฌ๋‹์˜ ์ฒซ๊ฑธ์Œ: NumPy์™€ Matplotlib๋กœ ์„ ํ˜•ํšŒ๊ท€ ๋ฐ์ดํ„ฐ ์‹œ๊ฐํ™”ํ•˜๊ณ  ๋ถ„์„ํ•˜๊ธฐ ์„ ํ˜• ํšŒ๊ท€ ๋ชจ๋ธ(Linear Regression)์˜ ๊ธฐ์ดˆ์ ์ธ ํŒŒ์ด์ฌ ์ฝ”๋“œ ์˜ˆ์ œ๋ฅผ ์‚ดํŽด๋ณด๋ฉฐ NumPy์™€ Matplotlib์˜ ํ™œ์šฉ๋ฒ•์„ ๋ฐฐ์›Œ๋ณด๋„๋ก ํ•˜์ž. ์ฝ”๋“œ ํ’€๋ฒ„์ „import numpy as npimport matplotlib.pyplot as pltplt.style.use('./deeplearning.mplstyle')# x_train is the input variable (size in 1000 square feet)# y_train is the target (price in 1000s of dollars)x_train = np.array([1.0, 2.0])y_train = np.array([300.0, 500.0])print(f"x_train = {x_train}")print(f"y_train =..