Machine Learning Algorithms: Supervised Learning Tip to Tail
Master supervised learning algorithms including decision trees, k-NN, and SVMs. Practical implementation with scikit-learn.
Master supervised learning algorithms including decision trees, k-NN, and SVMs. Practical implementation with scikit-learn.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Machine Learning: Algorithms in the Real World Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.7
(410 ratings)
16,715 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
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What you'll learn
Implement classification algorithms using decision trees and k-NN
Master regression techniques and support vector machines
Optimize model performance through parameter tuning
Assess and validate machine learning models
Apply supervised learning to real-world problems
Skills you'll gain
This course includes:
3.1 Hours PreRecorded video
9 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course covers supervised learning algorithms from theory to implementation. Students learn to implement and optimize classification and regression techniques using scikit-learn. Topics include decision trees, k-nearest neighbors, support vector machines, logistic regression, and neural networks. The curriculum emphasizes practical applications, model assessment, and performance optimization through hands-on programming exercises.
Classification using Decision Trees and k-NN
Module 1 · 3 Hours to complete
Functions for Fun and Profit
Module 2 · 1 Hours to complete
Regression for Classification: Support Vector Machines
Module 3 · 2 Hours to complete
Contrasting Models
Module 4 · 1 Hours to complete
Fee Structure
Instructor
Senior Scientific Advisor at the Alberta Machine Intelligence Institute (Amii), working to nurture productive relationships between industry and academia
working to nurture productive relationships between industry and academia and mainly focused on reinforcement learning, received her Master’s in Computing Science under the supervision of Dr. Richard Sutton, one of the field’s pioneer
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4.7 course rating
410 ratings
Frequently asked questions
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