Overview
Dive into a comprehensive tutorial on supervised machine learning, focusing on two powerful algorithms: logistic regression and Naive Bayes classifiers. Explore the fundamentals of logistic regression, including its applications in binary and multi-class classification, advantages, and limitations. Learn about Naive Bayes classifiers, their probabilistic approach, and effectiveness in various applications such as spam filtering and sentiment analysis. Gain insights into the strengths and weaknesses of both algorithms, their implementation techniques, and real-world use cases. Enhance your understanding of these essential supervised learning methods to develop practical skills in data classification and predictive modeling.
Syllabus
Supervised Machine Learning Tutorial | Logistic Regression | Naive Bayes Classifier
Taught by
Great Learning