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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

405 个评分


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....



May 14, 2022

This is an excellent course which goes into some depth on the different ML models and underlying complexity but it avoids getting bogged down into the details too much.


Apr 11, 2020

Excellent course. In which I had in-depth knowledge of all algorithms and the way she explained attracts to listen except for her spontaneity and speed in progressing.


1 - Machine Learning Algorithms: Supervised Learning Tip to Tail 的 25 个评论(共 65 个)

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Oct 10, 2019