Explore the application of classification algorithms in this comprehensive video lecture. Dive into comparisons between popular classification techniques, examining factors that influence their performance. Learn to evaluate algorithm effectiveness through a real-world case study on employee promotion prediction. Begin with an introduction to classification concepts, then progress through data preprocessing, logistic regression, support vector machines, k-nearest neighbors, Naive Bayes, decision trees, and random forests. Gain practical insights into implementing these algorithms for solving real-time classification problems across various domains.
Overview
Syllabus
Introduction.
Parameters For Comparison.
Promotion Problem Statement.
Preprocessing Data.
Logistic Regression.
Support Vector Machine.
K Nearest Neighbours.
Naive Bayes.
Decision Tree.
Random Forest.
Taught by
Great Learning
