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1
Better Deep Learning: Train Faster, Reduce Overfitting, and Make Better Predictions
machinelearningmastery.com
Jason Brownlee
dataset
function
models
import
neural
accuracy
listing
activation
weights
layer
network
testx
n_train
testy
classification
trainx
trainy
dense
rate
mlp
networks
model.add
output
layers
weight
regularization
verbose
evaluate
input
error
epochs
noise
pyplot.plot
gradient
average
batch
history.history
curves
relu
values
define
dropout
predictions
sequential
range
blobs
test_acc
validation
epoch
algorithm
年:
2018
语言:
english
文件:
PDF, 9.42 MB
您的标签:
0
/
0
english, 2018
2
Better Deep Learning: Train Faster, Reduce Overfitting, and Make Better Predictions
Machine Learning Mastery
Jason Brownlee
dataset
function
models
import
neural
accuracy
listing
activation
weights
layer
network
testx
n_train
testy
classification
trainx
trainy
dense
rate
mlp
networks
model.add
output
layers
weight
regularization
verbose
evaluate
input
error
epochs
noise
pyplot.plot
gradient
average
batch
history.history
curves
relu
values
define
dropout
predictions
sequential
range
blobs
test_acc
validation
epoch
algorithm
年:
2019
语言:
english
文件:
PDF, 9.42 MB
您的标签:
5.0
/
5.0
english, 2019
3
백견불여일타 딥러닝 입문 with 텐서플로우
조휘용
해봐요
모델
import
모델을
학습
activation
데이터
데이터를
dense
x_train
model.add
모델의
그림
컨볼루션
conv2d
y_train
함수를
relu
사용하여
acc
이미지
신경망
텐서플로우
케라스
함수
사용할
inputs
검증
sequential
각
데이터셋
성능을
다중
epochs
mnist
padding
사용하는
epoch
손실
형태를
batch_size
val_loss
됩니다
결과를
사용하기
다음과
데이터의
햄버거
input
사용합니다
年:
2020
语言:
korean
文件:
PDF, 13.89 MB
您的标签:
0
/
5.0
korean, 2020
4
Python数据科学速查表 - Keras
iBooker it-ebooks
it-ebooks
model2
activation
import
dense
model.add
model3
relu
dropout
x_test4
batch_size
metrics
num_classes
optimizer
sequential
accuracy
conv2d
rmsprop
to_categorical
x_train4
归
keras.layers
model.compile
numpy
y_test
络
网
binary_crossentropy
epochs
input_dim
keras.models
kernel_initializer
maxpooling2d
sigmoid
train_test_split
x_train2
y_test3
y_test4
y_train
y_train3
y_train4
测
练
训
categorical_crossentropy
cifar10
compile
early_stopping_monitor
earlystopping
embedding
flatten
年:
2018
语言:
chinese
文件:
PDF, 395 KB
您的标签:
0
/
0
chinese, 2018
5
DataCamp Keras Cheat Sheet
iBooker it-ebooks
it-ebooks
model2
activation
import
dense
model.add
model3
relu
dropout
sequential
x_test4
batch_size
metrics
num_classes
optimizer
accuracy
conv2d
numpy
rmsprop
to_categorical
x_train4
classification
keras.layers
mlp
model.compile
neural
y_test
binary_crossentropy
compile
epochs
evaluate
input_dim
keras.models
kernel_initializer
maxpooling2d
network
padding
python
sets
sigmoid
train_test_split
x_train2
y_test3
y_test4
y_train
y_train3
y_train4
arrays
binary
categorical_crossentropy
cifar10
年:
2018
语言:
english
文件:
PDF, 137 KB
您的标签:
0
/
0
english, 2018
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