Simple Neural Network using Tensorflow

tensorflow_simple_neural_network.py

# Imports
import tensorflow as tf
import numpy as np
from tensorflow import keras

# Define and compile the Neural Network (NN)
model = tf.keras.Sequential([keras.layers.Dense(units=1, input_shape=[1])]) # Only 1 neuron

# Compile the NN
model.compile(optimizer='sgd', loss='mean_squared_error')

# Simple test data
xs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)
ys = np.array([-2.0, 1.0, 4.0, 7.0, 10.0, 13.0], dtype=float)

# Train the NN
model.fit(xs, ys, epochs=50)

# Predict result for new number
print(model.predict([10.0]))