Machine Learning Algorithms - Interactive Study Guide

Machine Learning in a nutshell

Teaching computers to learn from data so they can make decisions or predictions.

Data → Learn → Model

Give examples, computer finds patterns, we use the model to predict on new data.

Everyday Uses

Recommendations, spam filters, face unlock, voice assistants.

Simple Warning

ML needs good data; garbage in → garbage out.

More Details (Syllabus Notes)

This short guide follows the CBSE Class 11 AI handbook. ML approaches can be supervised, unsupervised or reinforcement-based; supervised tasks include regression and classification; unsupervised tasks include clustering and dimensionality reduction.

Model

A model is a learned function that maps input to output. We evaluate models using measures like accuracy (classification) or mean squared error (regression).

Training & Testing

We split data into train and test sets; train to learn parameters and test to check performance on unseen data.

Ethics & Data

Always consider privacy, bias, and fairness when using datasets — these points are highlighted in the Teacher Handbook.

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