Искусственный интеллект, методы и технологии информационной безопасности
Международная научно-техническая конференция «Практическое применение технических и
цифровых технологий и их инновационных решений», ТАТУФФ, Фергана, 4 мая 2023 г.
468
model = tf.keras.models.Sequential([
tf.keras.layers.Flatten(input_shape=(28, 28)),
tf.keras.layers.Dense(128, activation='relu'),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Dense(10)
])
predictions = model(x_train[:1]).numpy()
print(predictions)
tf.nn.softmax(predictions).numpy()
loss_fn
=
tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)
model.compile(optimizer='adam',
loss=loss_fn,
metrics=['accuracy'])
model.fit(x_train, y_train, epochs=5)
model.evaluate(x_test, y_test, verbose=2)
In this example, we first load the MNIST dataset,
which consists of
images of handwritten digits. We then normalize the pixel values to be between
0 and 1.
Next, we define a neural network using the Sequential API. This network
has two dense layers and a dropout layer to prevent overfitting. The final layer
has 10 output nodes, one for each digit.
We then make a prediction on the first image in the training set and print
the result. We also apply the softmax function to the output to get a probability
distribution over the digits.
We define the loss function and compile the model with the Adam
optimizer. We then train the model for 5 epochs and evaluate its performance on
the test set.
Sun’iy intelekt, axborot xavfsizligi texnikasi va texnologiyalari
Международная научно-техническая конференция «Практическое применение технических и
цифровых технологий и их инновационных решений», ТАТУФФ, Фергана, 4 мая 2023 г.
469
This is just a simple example of what TensorFlow can do. The library is
capable of much more complex computations,
including image recognition,
natural language processing, and more.
TensorFlow is a powerful library for building and training machine
learning models. It provides a wide range of tools
and APIs for building and
deploying models, making it a popular choice for both beginners and experts in
the field.
In this guide, we have provided an overview of TensorFlow and how to
get started using it. We encourage you to explore
the library further and
experiment with building your own models. With its scalability and flexibility,
TensorFlow has the potential to revolutionize the field of machine learning and
drive innovation in many industries.
