Supervised machine learning is used to build predictive models using labeled data. In this course, you will learn from data professionals with over 18 years of experience through live classes.
Prerequisites:
- Basic understanding of Python programming
- Familiarity with datasets and basic data concepts
- Basic knowledge of statistics and probability
- Interest in machine learning and data analysis
What Will You Learn:
- Fundamentals of supervised machine learning
- Understanding labeled datasets
- Linear regression for prediction
- Logistic regression for classification
- Decision trees and random forests
- K-nearest neighbors (KNN)
- Support vector machines (SVM)
- Model evaluation techniques
