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Learner Reviews & Feedback for Machine Learning Algorithms: Supervised Learning Tip to Tail by Alberta Machine Intelligence Institute

34 ratings
4 reviews

About the Course

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. To be successful, you should have at least beginner-level background in Python programming (e.g., be able to read and code trace existing code, be comfortable with conditionals, loops, variables, lists, dictionaries and arrays). You should have a basic understanding of linear algebra (vector notation) and statistics (probability distributions and mean/median/mode). This is the second course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute....

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1 - 4 of 4 Reviews for Machine Learning Algorithms: Supervised Learning Tip to Tail

By Luiz C

Sep 11, 2019

Had higher expectations. Concepts not well and clearly explained. Notebooks bugged (we are actually warned about it), but even so not so interesting. Plan of the Course not so rational: why include the one section about model parameters on its own, rather than for each model.

I give it a 3 as the Instructor is smily and engaging, but it's a 2.5 mark (I have done another ML MOOC on another concurrent platform about the same topic, and the quality was much higher)

By M J

Oct 30, 2019

Great course! I received so much useful information from AMII.

By Miguel A S M

Oct 15, 2019


Teach you practical stuff that other courses don't.

By Cheng H Z

Oct 10, 2019

Explained things clearly