I visited a website and saw this computer code
import tensorflow as tf from tensorflow.keras import datasets, layers, models
import matplotlib.pyplot as plt
train_images, train_labels), (test_images, test_labels) = datasets.cifar10.load_data()
model.compile(optimizer=‘adam’, loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True), metrics=[‘accuracy’])history = model.fit(train_images, train_labels, epochs=10, validation_data=(test_images, test_labels))
What is train_label?
Hi @david_lopez1 ,
train_labels variable is a list of integers that identify the class of each image in the training set. The CIFAR-10 dataset contains 60,000 images, each of which is one of 10 classes: airplane, car, bird, cat, dog, deer, frog, horse, ship, or truck.
train_labels variable is used to train the model to associate images with their corresponding classes. Once the model has been trained, it can be used to make predictions about the class of new images.
I hope this is helpful!