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Bewertung und Feedback des Lernenden für Optimizing Machine Learning Performance von Alberta Machine Intelligence Institute
45 Bewertungen
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This course synthesizes everything your have learned in the applied machine learning specialization. You will now walk through a complete machine learning project to prepare a machine learning maintenance roadmap. You will understand and analyze how to deal with changing data. You will also be able to identify and interpret potential unintended effects in your project. You will understand and define procedures to operationalize and maintain your applied machine learning model. By the end of this course you will have all the tools and understanding you need to confidently roll out a machine learning project and prepare to optimize it in your business context.
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 final course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute (Amii).
Top-Bewertungen
MB
19. Jan. 2022
Very good course! I appreciate the opportunity to learn more from Alberta Machine Intelligence Institute. On the downside, Peer-graded Assignment block our progress on the course.
PZ
21. März 2021
One of the finest courses about Machine Learning Optimization. The course walks you through almost all possible scenarios that will need optimization.
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