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this into a learning approach-based AI machine. The machine would analyse the various images and come up
with various patterns it observes in these 1000 images, such as wing span, size of butterflies, or colour.

Learning Based AI Mod
Learning Based AI Modelel

Training Dataset Using

Unlabelled data
Learning Approach AI Model

Output

Unlabelled Dataset

Clustering output based on pattern observed by the machine

Example 2: Another example of a learning-based approach is Spam filters in email software. A learning-based
spam email filter is a computer program that determines if an incoming email is spam or not. Instead of being
manually programmed with specific rules to identify spam, this filter learns from examples of emails that have
already been marked as spam or legitimate during a training phase.

Email Inbox

Spam
Email Recipient
Filter

Spam Email Spam Folder
In the training phase, the filter receives a large set of emails, each labelled as either spam or non-spam. It looks at
different aspects of these emails, like the words and phrases used, the address of the sender, and whether these
emails have attachments or not. By using machine learning algorithms, the filter learns to recognise patterns
that help it tell the difference between spam and legitimate emails.
After training, the filter can categorise new incoming emails as spam or not spam, based on the patterns it has
learned. This helps users manage their email inboxes more efficiently. It also adds new emails that the user tags
as spam and adds them into the training dataset for the next iteration of training. Thus, it learns with experience
and usage over a period.

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