Deep learning is a powerful tool that can be used to solve a wide variety of problems. However, it can be difficult to get started with deep learning, especially if you don't have a background in machine learning.
This article will walk you through a simple example of how to create a neural network to learn the relationship between two numbers. This is a classic "hello world" example of deep learning, and it is a great way to get started with this powerful technology.
The setup
The first step is to import the necessary libraries. We will be using TensorFlow and NumPy, which are two popular libraries for deep learning and numerical computing.
import tensorflow as tf
import numpy as np
Defining the neural network
The next step is to define the neural network. We will use a simple neural network with one layer and one neuron. The input to the neural network will be a single number, and the output will be a single number.
model = tf.keras.Sequential([tf.keras.layers.Dense(units=1, input_shape=[1])])
Compiling the neural network
Once we have defined the neural network, we need to compile it. This involves specifying the loss function and the optimizer. The loss function measures how well the neural network is performing, and the optimizer is used to update the weights of the neural network.
model.compile(loss='mse', optimizer='sgd')
Providing the data
The next step is to provide the neural network with some data. We will use a dataset of six points, where each point consists of a single input and a single output.
xs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)
ys = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)
Training the neural network
Now we can train the neural network. This involves feeding the neural network with the data and letting it learn the relationship between the input and the output.
model.fit(xs, ys, epochs=500)
Making a prediction
Once the neural network has been trained, we can use it to make predictions. For example, we can predict the output for an input of 10.
print(model.predict([10.0]))
The output of the neural network is 18.999999. This is close to the expected output of 19, but it is not exactly 19. This is because the neural network is dealing with probabilities, and there is always some uncertainty involved in making predictions.
This article has shown you how to create a simple neural network to learn the relationship between two numbers. This is a classic "hello world" example of deep learning, and it is a great way to get started with this powerful technology.
We will use Google Colaboratory, which is a free online environment that runs in the browser. You can use Colaboratory to run, edit, and inspect your Python code.
