Futuristic Digital Aesthetic with Neon Interconnectivity – AI Generated Video | Hailuo AI

Generate & Play Hailuo AI video：import tensorflow as tf from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense, Flatten from tensorflow.keras.datasets import mnist from tensorflow.keras.utils import to_categorical # Loading the MNIST dataset (x_train, y_train), (x_test, y_test) = mnist.load_data() # Normalizing the data (scale 0-1) x_train = x_train / 255.0 x_test = x_test / 255.0 # One-hot encoding for the labels y_train = to_categorical(y_train, 10) y_test = to_categorical(y_test, 10) # Building a simple neural network model model = Sequential([ Flatten(input_shape=(28, 28)), # Flattening the 28x28 pixel input into a vector of 784 elements Dense(128, activation='relu'), # Hidden layer with 128 neurons and ReLU activation function Dense(10, activation='softmax') # Output layer with 10 neurons (one for each class) and softmax function ]) # Compiling the model model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy']) # Training the model model.fit(x_train, y_train, epochs=5, batch_size=32) # Evaluating the model loss, accuracy = model.evaluate(x_test, y_test) print(f'Loss: {loss:.4f}, Accuracy: {accuracy:.4f}')