Neural Network & It’s Use Cases in Industry

What is Neural Network ?

A neural network is a network or circuit of neurons, or in a modern sense, artificial neural network , composed of artificial neural or nodes. Thus a Neural Network is either a biological neural network , made up of real biological neurons, or an artificial neural network, for solving artificial intelligence(AI) problems.

• The input layer is responsible for receiving the inputs. These inputs can be loaded from an external source such as a web service or a csv file.
• Hidden layers reside in-between input and output layers and this is the primary reason why they are referred to as hidden. The word “hidden” implies that they are not visible to the external systems and are “private” to the neural network.
• The output layer is responsible for producing the final result. There must always be one output layer in a neural network.

Applications:-

Neural networks can be used in different fields. The tasks to which artificial neural networks are applied tend to fall within the following broad categories:

• Function approximation, or regression analysis, including time series prediction and modeling.
• Classification, including pattern and sequence recognition, novelty detection and sequential decision making.
• Data processing, including filtering, clustering, blind signal separation and compression.

Tasks of Neural Network

Neural networks are highly valuable because they can carry out tasks to make sense of data while retaining all their other attributes. Here are the critical tasks that neural networks perform:

• Classification: NNs organize patterns or datasets into predefined classes.
• Prediction: They produce the expected output from given input.
• Clustering: They identify a unique feature of the data and classify it without any knowledge of prior data.
• Association: You can train neural networks to “remember” patterns. When you show an unfamiliar version of a pattern, the network associates it with the most comparable version in its memory and reverts to the latter.

Use Cases:-

Facebook — Chatbot Army:- Although Facebook’s Messenger service is still a little…contentious (people have very strong feelings about messaging apps, it seems), it’s one of the most exciting aspects of the world’s largest social media platform. That’s because Messenger has become something of an experimental testing laboratory for chatbots.

Some chatbots are virtually indistinguishable from humans when
conversing via text

Any developer can create and submit a chatbot for inclusion in Facebook Messenger. This means that companies with a strong emphasis on customer service and retention can leverage chatbots, even if they’re a tiny startup with limited engineering resources.

Of course, that’s not the only application of machine learning that Facebook is interested in. AI applications are being used at Facebook to filter out spam and poor-quality content.

Thank you :)