Free
CourseMachine Learning: K-Nearest Neighbors
Sharpen your machine learning skills by learning how to prepare, implement, and assess the K-Nearest Neighbors algorithm.
This course includes
This course includes
Skill level
BeginnerTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary3 hoursProjects
1Prerequisites
None
About this course
Continue your Machine Learning journey with Machine Learning: K-Nearest Neighbors (KNN). Learn how to classify unknown data points based on their similarity to other, known, data points. Use distance and proximity to validate your predictions, and get started with classification techniques.
Skills you'll gain
Prepare data for a KNN model
Explain distance and proximity
Implement and assess a KNN model
Syllabus
Classification: K-Nearest Neighbors
K-Nearest Neighbors is a supervised machine learning algorithm for classification. You will implement and test this algorithm on several datasets.
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Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
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