做se要明白網(wǎng)站,小紅書關(guān)鍵詞排名怎么做,網(wǎng)站建設(shè)人員工作要求,英文網(wǎng)站設(shè)計(jì)哪里好文章目錄 基礎(chǔ)MLP網(wǎng)絡(luò)1.回歸任務(wù)2.分類任務(wù)mlp及深度學(xué)習(xí)常見(jiàn)技巧1.基礎(chǔ)模型2.權(quán)重初始化3.激活函數(shù)4.優(yōu)化器5.批正則化6.dropout基礎(chǔ)MLP網(wǎng)絡(luò)
1.回歸任務(wù) import tensorflow as tf
import tensorflow.keras as keras
import tensorflow.keras.layers as layers# 導(dǎo)入數(shù)據(jù)
(x_t…
文章目錄
基礎(chǔ)MLP網(wǎng)絡(luò)
1.回歸任務(wù)
2.分類任務(wù)
mlp及深度學(xué)習(xí)常見(jiàn)技巧
1.基礎(chǔ)模型
2.權(quán)重初始化
3.激活函數(shù)
4.優(yōu)化器
5.批正則化
6.dropout
基礎(chǔ)MLP網(wǎng)絡(luò)
1.回歸任務(wù)
import tensorflow as tf
import tensorflow.keras as keras
import tensorflow.keras.layers as layers# 導(dǎo)入數(shù)據(jù)
(x_train, y_train), (x_test, y_test) = keras.datasets.boston_housing.load_data()
print(x_train.shape, ' ', y_train.shape)
print(x_test.shape, ' ', y_test.shape)#%%# 構(gòu)建模型model = keras.Sequential([layers.Dense(32, activation='sigmoid', input_shape=(13,)),la
