WHAT IS MODELLING ?

WHAT IS MODELLING ?

DEFINITION :

Modelling is defined as the process of designing decision-making algorithms that has to be trained on a set of data ( which was acquired at the data acquisition stage for the problem you scoped in the problem-scoping stage ) and apply that learning to recognise certain types of patterns.

Once the data is visualized ans trends are formed,we need to work with algorithms to prepare the AI model.This can be done by designing our own models or using the existing AI models.Let us first understand the following important terms:

1. ARTIFICIAL INTELLIGENCE :

AI refers to any technique that enables computers to mimic or imitate,develop and demonstrate human intelligence.They are machines that can perform tasks that they are programmed for.AI enables machines to think without any human intervention.

2.MACHINE LEARNING:

Machines need to learn the ways of humans by learning the techniques and processes.So machine learning is a subset of AI that uses statistical methods that enable machines to improve with experiences.So machines learn from their mistakes and take them into consideration in the next iteration,this way they keep improving with experience.For example,snapchat filters and netflix recommendations.

3.DEEP LEARNING:

Machines can draw meaningful inferences from large volumes of datasets.In deep learning,the machine is trained with a huge amount of data which helps in train itself.Deep learning is a machine learning algorithm that is inspired by the functionality of our brain cells called neurons. for example,Google translate,Image recognition in social media apps.

AI is an umbrella term that holds machine learning and deep learning .Deep learning follows a specific learning approach which is a subset of a machine learning comprising multiple machine learning algorithms.

These are the three important terms of modelling.

WITHIN THIS,THE CHAPTER ENDS....