This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbours and support vector machines are optimally used. Learners will also gain skills to contrast the practical consequences of different data preparation steps and describe common production issues in applied ML.
About this Course
- 5 stars76.04%
- 4 stars18.51%
- 3 stars3.20%
- 2 stars0.98%
- 1 star1.23%
TOP REVIEWS FROM MACHINE LEARNING ALGORITHMS: SUPERVISED LEARNING TIP TO TAIL
really good, wish it had covered random forest and decision trees and other supervised models as well.
Great course! I received so much useful information from AMII.
Many useful information but need some more explanation, overall awesome
It's a nice course for those who likes to learn the supervised machine learning algorithms with practical experience.
About the Machine Learning: Algorithms in the Real World Specialization
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Specialization?
Is financial aid available?
More questions? Visit the Learner Help Center.