Mathematical Foundation For Machine Learning and AI
Learn the core mathematical concepts for machine learning and learn to implement them in R and python
4.34 (1291 reviews)
7 546
students
4.5 hours
content
Dec 2018
last update
$44.99
regular price
What you will learn
Refresh the mathematical concepts for AI and Machine Learning
Learn to implement algorithms in python
Understand the how the concepts extend for real world ML problems
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Our Verdict
This course offers an accessible approach to building a mathematical foundation for machine learning and artificial intelligence. While it provides a concise review of essential topics, it may leave advanced learners wanting more depth. Still, its value lies in quickly familiarizing students with the necessary math through code examples and visualizations. However, be prepared for occasional errors or unclear explanations that might require external resources to clarify.
What We Liked
- Covers mathematical concepts critical for machine learning and AI
- Logical order of topics with useful code examples
- Effective introduction to essential ML-related math for beginners
- Addresses specific needs of those looking for quick Math review
Potential Drawbacks
- Lacks in-depth explanations and may require additional resources
- Some mistakes in the material and occasional unclear expressions
- Limited, high-level overview which may not benefit ML/AI professionals
- Missing some fundamental concepts like matrix division and tensor details
Related Topics
1713894
udemy ID
25/05/2018
course created date
20/11/2019
course indexed date
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