fromkeras.layersimportLSTMmodel=Sequential()model.add(embedding_layer)model.add(LSTM(32))#当结果是输出多个分类的概率时，用softmax激活函数,它将为30个分类提供不同的可能性概率值model.add(layers.Dense(...

fromkeras.layersimportSimpleRNNmodel=Sequential()model.add(embedding_layer)model.add(SimpleRNN(32))#当结果是输出多个分类的概率时，用softmax激活函数,它将为30个分类提供不同的可能性概率值model.add(lay...

importpandasaspddf=pd.read_json('/Users/chenyi/Documents/News_Category_Dataset.json',lines=True)df.head()df.category=df.category.map(lambdax:"WORLDPOST"ifx=="TH...

importmatplotlib.pyplotaspltimportnumpyasnpimportmatplotlib.mlabasmlabimportmathmu=0variance=1sigma=math.sqrt(variance)x=np.linspace(mu-3*sigma,mu+3*sigma,100)p...

importnumpyasnpsamples=['Thecatjumpoverthedog','Thedogatemyhomework']#我们先将每个单词放置到一个哈希表中token_index={}forsampleinsamples:#将一个句子分解成多个单词forwordinsample.split():ifw...

defconv_(img,conv_filter):filter_size=conv_filter.shape[1]result=numpy.zeros((img.shape))print('loopr:',numpy.uint16(numpy.arange(filter_size/2.0,img.shape[0]-f...

fromkeras.preprocessingimportimagefromkeras.preprocessing.imageimportImageDataGeneratorimportosimportmatplotlib.pyplotaspltdatagen=ImageDataGenerator(rotation_r...

importosbase_dir='/Users/apple/Documents/cat-and-dog'train_cats_dir=os.path.join(base_dir,'training_set/cats')train_dogs_dir=os.path.join(base_dir,'training_set...

fromkerasimportlayersfromkerasimportmodelsmodel=models.Sequential()#首层接收2维输入model.add(layers.Conv2D(32,(3,3),activation='relu',input_shape=(28,28,1)))model.add(...

importpandasaspddata_path='/Users/chenyi/Documents/housing.csv'housing=pd.read_csv(data_path)housing.info()housing.head()housing.describe()housing.hist(bins=50,...

importpandasaspddf=pd.read_json('/Users/chenyi/Documents/News_Category_Dataset.json',lines=True)df.head()categories=df.groupby('category')print("totalcategories...

fromkeras.datasetsimportimdb#num_words表示加载影评时，确保影评里面的单词使用频率保持在前1万位，于是有些很少见的生僻词在数据加载时会舍弃掉(train_data,train_labels),(test_data,test_labels)=imdb.load_data(num_wor...

classNeuralNetWork:def__init__(self):'''初始化网络，设置输入层，中间层，输出层的节点数'''passdeffit(self):'''根据训练数据，不断更新神经网络层之间的链路权重'''passdefevaluate(self):'''输入新数据，网络给出对新数据的判断结果'''p...

#绘制步调函数图像importmatplotlib.pyplotaspltx=[1,2,3,4]y=[0,1,2,3]plt.step(x,y)plt.show() importnumpyasnpimportpylabaspltfrommatplotlibimportpylab#设置simoid函数计算流程d...

importnumpyasnp#构建一个含有一个常数12的0维张量x=np.array(12)print(x)#ndim表示张量的维度print(x.ndim)x1=np.array([11,12,13])print(x1)print(x1.ndim)x2=np.array([[11,12,13],[14,15,16]...