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Bewertung und Feedback des Lernenden für Machine Learning Algorithms: Supervised Learning Tip to Tail von Alberta Machine Intelligence Institute

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Über den Kurs

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....

Top-Bewertungen

TH

14. Mai 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.

DS

6. Mai 2020

Excellent course for an overview of different ML algorithms. The course is made from a perspective of giving insights in process and not too many mathematical details.

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