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返回到 Machine Learning Algorithms: Supervised Learning Tip to Tail

学生对 Alberta Machine Intelligence Institute 提供的 Machine Learning Algorithms: Supervised Learning Tip to Tail 的评价和反馈

30 个评分
4 个审阅


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....



1 - Machine Learning Algorithms: Supervised Learning Tip to Tail 的 4 个评论(共 4 个)

创建者 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)

创建者 Cheng H Z

Oct 10, 2019

Explained things clearly

创建者 M J

Oct 30, 2019

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

创建者 Miguel A S M

Oct 15, 2019


Teach you practical stuff that other courses don't.