import numpy as np import pandas as pd import matplotlib.pyplot as plt

from tensorflow.keras.datasets import cifar10

(x_train, y_train), (x_test, y_test) = cifar10.load_data() print(x_train.shape)

plt.imshow(x_train[1]) plt.show() plt.imshow(x_train[2]) plt.show()

https://keras.io/api/layers/convolution_layers/convolution2d/ https://www.tensorflow.org/tutorials/images/cnn

from tensorflow.keras import Sequential from tensorflow.keras.layers import Dense, Flatten, Conv2D model = Sequential() model.add(Conv2D(32, (3,3), activation="relu")) #filters 32,kernel_size matrice (3,3) model.add(Flatten()) #mettre dans un vect model.add(Dense(300, activation='relu')) model.add(Dense(10, activation='softmax')) #une couche dense

import tensorflow as tf

from tensorflow.keras.losses import SparseCategoricalCrossentropy as s2c model.compile(optimizer='sgd', loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True), metrics=['accuracy'])

model.fit