写一段神经网络预测代码
时间: 2023-12-01 22:53:08 浏览: 19
Sure, I can provide you with a basic code snippet for neural network prediction using Python:
```
import numpy as np
import tensorflow as tf
# Define the input data
input_data = ... # your input data here
# Define the neural network model
model = tf.keras.models.Sequential([
tf.keras.layers.Dense(64, activation='relu'),
tf.keras.layers.Dense(64, activation='relu'),
tf.keras.layers.Dense(1)
])
# Compile the model
model.compile(loss='mean_squared_error', optimizer=tf.keras.optimizers.Adam(0.1))
# Train the model
model.fit(input_data, epochs=10)
# Generate predictions
predictions = model.predict(input_data)
```
This code defines a simple neural network model with two hidden layers, trains it on the input data using a mean squared error loss function and the Adam optimizer, and generates predictions for the same input data. Of course, this is just a basic example and you should adjust the code to fit your own needs depending on your data, requirements, and use case. Let me know if you have any other questions!