Neural Networks in Machine Learning

March 25, 2017
Posted in Journal
March 25, 2017 O2O Pro Management

Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data. It is also one of the learning algorithms used within machine learning. They consist of different layers for analyzing and learning data. The neural networks are information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information.

Why do we use neural network?

A trained neural network can be thought of as an “expert” in the category of information it has been given to analyze. This expert can then be used to provide projections given new situations of interest and provide predictions of situation.

Other advantages include:

Adaptive learning: An ability to learn how to do tasks based on the data given for training or initial experience.

Self-Organization: Create its own organization or representation of the information it receives during learning time.

Real Time Operation: Computations may be carried out in parallel, and special hardware devices are being designed and manufactured which take advantage of this capability.The data created by neural network helps in machine learning.  Depending on the nature of learning system, machine learning can be divided into the below,

Supervised learning: The computer is presented with example inputs and their desired outputs, given by a “teacher”, and the goal is to learn a general rule that maps inputs to outputs.

Unsupervised learning: No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning).

Reinforcement learning: A computer program interacts with a dynamic environment in which it must perform a certain goal (such as driving a vehicle or playing a game against an opponent. The program is provided feedback in terms of rewards and punishments as it navigates its problem space.

With the combination of neural networks, algorithm and machine learning , it helps in the Artificial intelligence(AI) field. It is not hard to see a robot with brains in the years to come.

Source: Wikipedia