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Let us explore the important domains of AI:

 Data Science (The Brain): It uses large amounts of data to make predictions or decisions. It
looks for patterns in data like numbers or text. For example, it helps companies understand
customer preferences by analysing shopping habits and is used for predicting sales and
spotting fraud.

 Computer Vision (The Eyes): This helps machines to see and understand images or videos.
For example, it is used in facial recognition on phones and in self-driving cars to help them see
the road and avoid obstacles.

 Natural Language Processing (The Ears): It allows machines to understand and respond to
human language. For example, it powers chatbots and voice assistants like Siri and Alexa.

PREDICTIVE TECHNIQUES IN AI

Prediction in AI is based on logic and mathematics, not magic. It works by using data collected in

the past to predict what might happen in the future. AI models are trained to identify patterns and
trends from this data and then apply them to new, unseen information.
For example, AI can predict the crop yield of a farm. By analysing factors like weather conditions,
soil quality and previous harvests, AI can estimate how much crop will be produced in a season.

This helps farmers plan better for the future.

INTRODUCTION TO CLASSIFICATION

Classification is a method used in AI where machines sort information into specific categories or
groups.

Consider an example, when you receive emails, your email service uses classification to decide
if an email is spam (unwanted email) or not spam (a valid message). The system is trained by
looking at examples of past emails, where it already knows if they are spam or not.

8 Artificial Intelligence (CT & AI)-VII