A friendly introduction to linear algebra for ML (ML Tech Talks)

In this session of Machine Learning Tech Talks, Tai-Danae Bradley, Postdoc at X, the Moonshot Factory, will share a few ideas for linear algebra that appear in the context of Machine Learning.

Chapters:
0:00 – Introduction
1:37 – Data Representations
15:02 – Vector Embeddings
31:52 – Dimensionality Reduction
37:11 – Conclusion

Resources:
Google Developer’s ML Crash Course on Collaborative Filtering → https://goo.gle/3pAVXM6
Eigenvectors and Eigenvalues” by 3Blue1Brown → https://goo.gle/3pECpWU
Introduction to Linear Algebra” (5th ed) by Gilbert Strang → https://goo.gle/2RFR1sP

Catch more ML Tech Talks → http://goo.gle/ml-tech-talks
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