Welcome to the TensorFlow getting started tutorial! In this guide, you will learn the basics of TensorFlow, a powerful open-source software library for data analysis and machine learning.
章节概述
安装 TensorFlow
Before you start, you need to install TensorFlow. You can find detailed installation instructions on the TensorFlow 官方网站.
pip install tensorflow
Hello World 示例
Here's a simple example to get you started with TensorFlow. This script will create a graph and run it to output "Hello, World!".
import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
print(hello)
TensorFlow 数据操作
TensorFlow provides a wide range of data operations. You can perform mathematical operations, create and manipulate tensors, and more.
TensorFlow 神经网络
TensorFlow is widely used for building neural networks. In this section, you will learn how to create and train a neural network.
import tensorflow as tf
model = tf.keras.Sequential([
tf.keras.layers.Dense(10, activation='relu', input_shape=(8,)),
tf.keras.layers.Dense(1, activation='sigmoid')
])
model.compile(optimizer='adam',
loss='binary_crossentropy',
metrics=['accuracy'])
# Assume `x_train` and `y_train` are your training data
model.fit(x_train, y_train, epochs=10)
For more detailed tutorials on neural networks, check out the TensorFlow 神经网络教程.
