ML Practice 3_2
Data Set12345678910111213141516171819import numpy as npperch_length = np.array( [8.4, 13.7, 15.0, 16.2, 17.4, 18.0, 18.7, 19.0, 19.6, 20.0, 21.0, 21.0, 21.0, 21.3, 22.0, 22.0, 22.0, 22.0, 22.0
Category: ML
ML Practice 3_1
Prepare DataData Set12345678910111213141516171819import numpy as npperch_length = np.array( [8.4, 13.7, 15.0, 16.2, 17.4, 18.0, 18.7, 19.0, 19.6, 20.0, 21.0, 21.0, 21.0, 21.3, 22.0, 22.0, 22.0
ML Practice 2_2
Prepare data with Numpy12345678fish_length = [25.4, 26.3, 26.5, 29.0, 29.0, 29.7, 29.7, 30.0, 30.0, 30.7, 31.0, 31.0, 31.5, 32.0, 32.0, 32.0, 33.0, 33.0, 33.5, 33.5, 34.0, 34.0, 34.5,
ML Practice 2_1
ML AlgorithmSupervised Learning(지도 학습) Input(입력; independent variable) & Target(타깃; dependent variable) Question with a correct answer Type 1: Classification(분류) Type 2: Regression(예측) Feature(특
ML Practice 1_3
Market and Machine LearningClassify Bream and SmeltBream Data123456bream_length = [25.4, 26.3, 26.5, 29.0, 29.0, 29.7, 29.7, 30.0, 30.0, 30.7, 31.0, 31.0, 31.5, 32.0, 32.0, 32.0, 33.0,