Python環境下基于機器學習的NASA渦輪風扇發動機剩餘使用壽命RUL預測程式為Python編寫，運作環境為Spyde

Python環境下基于機器學習的NASA渦輪風扇發動機剩餘使用壽命RUL預測

程式為Python編寫，運作環境為Spyder IDE，采用8種機器學習方法對NASA渦輪風扇發動機進行剩餘使用壽命RUL預測，8種方法分别為：Linear Regression，SVM regression，Decision Tree regression，KNN model，Random Forest，Gradient Boosting Regressor，Voting Regressor，ANN Model。

所用子產品如下：

import pandas as pd

import seaborn as sns

import numpy as np

import matplotlib.pyplot as plt

from sklearn.preprocessing import StandardScaler

from sklearn.model_selection import train_test_split

from sklearn.linear_model import LinearRegression

from sklearn.svm import SVR

from sklearn.tree import DecisionTreeRegressor

from sklearn.ensemble import RandomForestRegressor

面包多代碼網頁連結

from sklearn.metrics import mean_squared_error, r2_score

import tensorflow as tf

from tensorflow.keras.layers import Dense