Linear Algebra Course – Mathematics for Machine Learning and Generative AI

Learn linear algebra in this course for beginners. This course covers the linear algebra skills needed for data science, machine learning, and AI, with a focus on practical applications and real-world examples. ✏️ Course developed by @LunarTech_ai ⭐️ Contents ⭐️ ⌨️

Intermediate - 365 min - AI & Data - freeCodeCamp.org

The full course: Learn Math for ML free

What you'll need

• Laptop stand: Screen at eye level for long study sessions.
• Noise-cancelling headphones: Focus through long video lessons.
• Second monitor: Video on one screen, practice on the other.
• Wireless keyboard and mouse: Comfortable for hours of typing.

Books

1. Mathematics for Machine Learning by Marc Peter Deisenroth - View on Amazon
2. Naked Statistics by Charles J. Wheelan - View on Amazon
3. Practical Statistics for Data Scientists by Peter Bruce - View on Amazon
4. The Art of Statistics by David Spiegelhalter - View on Amazon
5. The Elements of Statistical Learning by Trevor Hastie - View on Amazon

Next lessons

• But what is a convolution? (23 min, 3Blue1Brown, Beginner)
• But what is the Fourier Transform? A visual introduction. (20 min, 3Blue1Brown, Beginner)
• How (and why) to take a logarithm of an image (45 min, 3Blue1Brown, Intermediate)
• Simulating an epidemic (23 min, 3Blue1Brown, Intermediate)
• But what are Hamming codes? The origin of error correction (20 min, 3Blue1Brown, Intermediate)
• Divergence and curl: The language of Maxwell's equations, fluid flow, and more (16 min, 3Blue1Brown, Intermediate)
• Solving Wordle using information theory (31 min, 3Blue1Brown, Intermediate)
• Taylor series | Chapter 11, Essence of calculus (22 min, 3Blue1Brown, Intermediate)