So? What's the story of this Neural thing?
These are artificial mathematical models which are inspired from our biological neural networks
so basically it has three layers
- Input Layer
- Output Layer
- Hidden Layers
all between cells are called as neurons
hidden layers do the most of the computations
basically all these layers are connected with which we call as channels
each channel has its own numerical weight
the inputs are multiplied with the corresponding weight of the channel and then each neuron in hidden layer has a value which is known as a bias
this bias is added to the multiplied value and is passed through a threshold function known as the activation function
the result coming from the activation function determines whether the neuron is activated or not
and then activated neurons participate in the further channels and they are propagated untill a final prediction is made
this propagation is known as the forward propagation
now at first we may not get the correct prediction as shown in the above picture, so now the error magnitude is calculated and based on that flow in reverse direction happen which is known as backward propagation
as this backward propagation takes place, the weights adjust themselves in such a way that they can predict correctly for a given data
in this manner huge labeled data is trained so that neural network can get proper weights and it can predict properly
it is a very time consuming and high computational process
What are the real time examples?
- Facial Recognition
- Forecasting (Weather forecast etc)
- Music Composition
Note
- Anything in real life, which follows a pattern kind of resemblance, a neural network can be applied and trained
- Neural Networks come under deep learning which is a subset of machine learning