Matrix multiplication implemented from scratch in Python | No NumPy, no libraries | Coding for ML

Published: 01 January 1970
on channel: Vizuara

351

Colab link: https://colab.research.google.com/dri...

I am excited to share my newest lecture on implementing matrix multiplication from scratch in Python. In this session, we are doing everything the manual way, which means no NumPy and no other libraries. It is an excellent hands-on exercise that deepens your understanding of lists (since matrices in Python are essentially lists of lists) and helps you build logical thinking skills step by step.

We explore how to check if two matrices can be multiplied by confirming that the number of columns of the first matrix matches the number of rows of the second matrix. Then we dive into the triple nested loop structure that performs the actual multiplication. By doing this entirely on your own, you will see how Python indexing works, how loops iterate, and how a result matrix can be constructed and updated element by element.

If you are looking to strengthen your Python skills with a solid, logic-focused exercise, this lecture is a great fit. It covers everything from dimension checks to the final summation of products. You will walk away with a clearer idea of how math translates into programming and a stronger foundation for tackling bigger projects in the future.

Feel free to let me know if you have any questions, and I would love to hear about your experience once you try coding this on your own.

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