Python Natural Language Processing

Training a simple neuron

Now it is time to see how we can use a single neuron for training by using the activation function, and let's understand the loss function to calculate the error in predicted output.

The main idea is defined as the error function, which actually tells us the degree of error in our prediction; we will actually try to make our error value as low as possible. So, in other words, we are actually trying to improve our prediction. During training, we use input and calculate the error by using the error function and update the weight of neurons and repeat our training process. We will continue this process until we get the minimum error rate of maximum, best, and accurate output.

The two most important concepts that we are ...