Learning Track

Supervised Learning - Regression

Regression is a type of supervised learning used to predict continuous numerical values, such as prices, temperatures, or quantities. Models learn relationships between input features and output values from labeled training data. This section covers fundamental regression algorithms, regularization techniques to prevent overfitting, and a hands-on project to apply your skills.

4 Lessons

1 Hours

1 Subtopic

Subtopics

Regression Algorithms - Predicting Continuous Values

Regression algorithms are machine learning methods used to predict continuous values based on input features. Techniques like Linear Regression, Decision Trees, Random Forests, and Gradient Boosting analyze relationships between variables to deliver accurate numeric predictions. They help solve real‑world problems such as forecasting prices, estimating demand, and analyzing trends with reliable, data‑driven insights.

4 lessons

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Lessons are available in the subtopics above.