create a neural network with two neurons tò interpolate in python

To create a neural network with two neurons to interpolate, you can use the numpy library in Python. Here's a simple example:

main.py
import numpy as np

# Define the neural network weights and biases
weights = np.array([[0.5], [-0.5]])  # 2x1 array
biases = np.array([0.5])  # 1D array

# Define the input data
input_data = np.array([[1], [2]])  # 2x1 array

# Perform the interpolation using the neural network
output = np.dot(weights.T, input_data) + biases

# Print the interpolated value
print(output)
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In this example, we define a neural network with two neurons. The weights and biases are initialized randomly. We then provide the input data (in this case, a 2x1 array) and perform the interpolation using the dot product of the weights and input data, and adding the biases. The resulting output is the interpolated value.

Note that this is a very basic example and does not involve training the neural network. If you want to train the network to improve its performance, you would need to use a suitable training algorithm such as gradient descent.

I hope this helps you get started with creating a neural network for interpolation in Python!