Overview
This course teaches learners about various classification algorithms such as decision tree, logistic regression, support vector machine, and naive Bayes classification. The focus is on both theoretical concepts and practical implementation using Python on datasets. By the end of the course, students will be able to apply these algorithms to classify new observations into different groups or classes. The intended audience for this course includes individuals interested in data science, machine learning, and artificial intelligence.
Syllabus
- Linear Regression.
- Logistic Regression with implementation in Python.
- Naive Bayes Algorithm with implementation in Python.
- Decision Tree with implementation in Python.
- Random Forest with implementation in Python.
- Support Vector Machine with implementation in Python.
Taught by
Great Learning