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...

importtensorflowastffromtensorflowimportkerasfromkerasimportSequential,datasets,layers,optimizers,metricsdefpreprocess(x,y):"""数据处理函数"""x=tf.cast(x,dtype=tf.flo...

importnumpyasnpimportmatplotlib.pyplotaspltfrommpl_toolkits.mplot3dimportAxes3Ddefhimmeblau(x):return(x[0]**2+x[1]-11)**2+(x[0]+x[1]**2-7)**2x=np.arange(-6,6,0....

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importtensorflowastfx=tf.constant(1.)w1=tf.constant(2.)b1=tf.constant(1.)w2=tf.constant(2.)b2=tf.constant(1.)withtf.GradientTape(persistent=True)astape:tape.wat...

importtensorflowastfx=tf.random.normal([2,4])w=tf.random.normal([4,3])b=tf.zeros([3])y=tf.constant([2,0])withtf.GradientTape()astape:tape.watch([w,b])#axis=1，表示...

    importtensorflowastfx=tf.random.normal([1,3])w=tf.ones([3,1])b=tf.ones([1])y=tf.constant([1])withtf.GradientTape()astape:tape.watch([w,b...

importtensorflowastfx=tf.random.normal([2,4])w=tf.random.normal([4,3])b=tf.zeros([3])y=tf.constant([2,0])withtf.GradientTape()astape:tape.watch([w,b])prob=tf.nn...

        importtensorflowastfa=tf.linspace(-10.,10.,10)awithtf.GradientTape()astape:tape.watch(a)y=tf.sigmoid(a)grads=tap...