我正在研究数据集上的人工神经网络算法。以下是我正在使用的数据集的来源。
我已经运行了代码，直到Feature Scaling，并且它成功运行了，没有任何问题。下面是我运行的代码：-
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv("C:\Machine learning\practices\Machine Learning A-Z Template Folder\Part 8 - Deep Learning\Section 39 - Artificial Neural Networks (ANN)\Artificial-Neural-Networks\Artificial_Neural_Networks\Churn1_Modelling.csv")
X = dataset.iloc[:, 3:13].values
y = dataset.iloc[:, 13].values
# Encoding categorical data
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelencoder_X_1 = LabelEncoder()
X[:, 1] = labelencoder_X_1.fit_transform(X[:, 1])
labelencoder_X_2 = LabelEncoder()
X[:, 2] = labelencoder_X_2.fit_transform(X[:, 2])
onehotencoder = OneHotEncoder(categorical_features = [1])
X = onehotencoder.fit_transform(X).toarray()
X = X[:, 1:]
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)
# Feature Scaling
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)
此后，我就跑了
import keras
这给了我错误，因为Python停止工作并且每次都重新启动内核。我已经安装了所有库和模块。以下是我已经安装的模块：-
Package Version
---------------------------------- -----------
alabaster 0.7.9
anaconda-clean 1.0
anaconda-client 1.5.1
anaconda-navigator 1.3.1
argcomplete 1.0.0
astroid 1.4.7
astropy 1.2.1
Babel 2.3.4
backports.shutil-get-terminal-size 1.0.0
backports.weakref 1.0rc1
beautifulsoup4 4.5.1
bitarray 0.8.1
blaze 0.10.1
bleach 1.5.0
bokeh 0.12.2
boto 2.42.0
Bottleneck 1.1.0
certifi 2018.8.24
cffi 1.7.0
chardet 3.0.4
chest 0.2.3
click 6.6
cloudpickle 0.2.1
clyent 1.2.2
colorama 0.3.7
comtypes 1.1.2
conda 4.5.11
conda-build 2.0.2
configobj 5.0.6
contextlib2 0.5.3
cryptography 1.5
cycler 0.10.0
Cython 0.24.1
cytoolz 0.9.0.1
dask 0.11.0
datashape 0.5.2
decorator 4.0.10
dill 0.2.5
docutils 0.12
dynd c328ab7
et-xmlfile 1.0.1
fastcache 1.0.2
filelock 2.0.6
Flask 0.11.1
Flask-Cors 2.1.2
gevent 1.1.2
greenlet 0.4.10
h5py 2.6.0
HeapDict 1.0.0
html5lib 0.9999999
idna 2.1
imagesize 0.7.1
ipykernel 4.5.0
ipython 5.1.0
ipython-genutils 0.1.0
ipywidgets 5.2.2
itsdangerous 0.24
jdcal 1.2
jedi 0.9.0
Jinja2 2.8
jsonschema 2.5.1
jupyter 1.0.0
jupyter-client 4.4.0
jupyter-console 5.0.0
jupyter-core 4.2.0
Keras 2.2.2
Keras-Applications 1.0.4
Keras-Preprocessing 1.0.2
keyring 13.2.1
lazy-object-proxy 1.2.1
llvmlite 0.13.0
locket 0.2.0
lxml 3.6.4
Markdown 2.2.0
MarkupSafe 0.23
matplotlib 1.5.3
menuinst 1.4.1
mistune 0.7.3
mkl-fft 1.0.4
mkl-random 1.0.1
mpmath 0.19
multipledispatch 0.4.8
nb-anacondacloud 1.2.0
nb-conda 2.0.0
nb-conda-kernels 2.0.0
nbconvert 4.2.0
nbformat 4.1.0
nbpresent 3.0.2
networkx 1.11
nltk 3.2.1
nose 1.3.7
notebook 4.2.3
numba 0.28.1
numexpr 2.6.7
numpy 1.15.1
numpydoc 0.8.0
odo 0.5.0
olefile 0.45.1
openpyxl 2.3.2
pandas 0.18.1
partd 0.3.6
path.py 0.0.0
pathlib2 2.1.0
patsy 0.4.1
pep8 1.7.0
pickleshare 0.7.4
Pillow 5.2.0
pip 18.0
pkginfo 1.3.2
ply 3.9
prompt-toolkit 1.0.3
protobuf 3.6.1
psutil 4.3.1
py 1.4.31
pyasn1 0.1.9
pycodestyle 2.4.0
pycosat 0.6.3
pycparser 2.14
pycrypto 2.6.1
pycurl 7.43.0.2
pyflakes 1.3.0
Pygments 2.2.0
pylint 1.5.4
pyOpenSSL 16.2.0
pyparsing 2.1.4
pytest 2.9.2
python-dateutil 2.5.3
pytz 2016.6.1
pywin32 220
PyYAML 3.12
pyzmq 15.4.0
QtAwesome 0.4.4
qtconsole 4.2.1
QtPy 1.5.0
requests 2.14.2
rope-py3k 0.9.4.post1
ruamel-yaml -VERSION
scikit-image 0.12.3
scikit-learn 0.19.2
scipy 1.1.0
setuptools 40.2.0
simplegeneric 0.8.1
singledispatch 3.4.0.3
six 1.11.0
snowballstemmer 1.2.1
sockjs-tornado 1.0.3
sphinx 1.4.6
spyder 3.3.1
spyder-kernels 0.2.4
SQLAlchemy 1.0.13
statsmodels 0.6.1
sympy 1.0
tables 3.2.2
tensorflow 1.2.0
Theano 1.0.2
toolz 0.8.0
tornado 4.4.1
traitlets 4.3.0
unicodecsv 0.14.1
wcwidth 0.1.7
Werkzeug 0.14.1
wheel 0.31.1
widgetsnbextension 1.2.6
win-unicode-console 0.5
wincertstore 0.2
wrapt 1.10.6
xlrd 1.0.0
XlsxWriter 0.9.3
xlwings 0.10.0
xlwt 1.1.2
请让我知道安装tensorflow和keras是否有问题，或者是否有其他错误，因为我无法继续使用人工神经网络算法来预测值。
谢谢。
答案 0 :(得分：1)
您似乎正在做SuperDataScience机器学习Az课程。
您的代码是正确的，并且运行良好。如果您正在使用anaconda内核（spyder IDE使用anaconda内核），请尝试通过pip3 install --upgrade tensorflow安装tensorflow。
根据您提供的库列表，您已经通过conda forge安装了tensorflow。
通过pip安装tensorflow后，尝试通过
import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))
您应该看到此输出Hello, TensorFlow!
现在，您可以通过运行以下代码keras
和pip install keras来尝试检查import keras的安装。您应该会看到以下输出：Using TensorFlow backend.
最好的问候