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 Subscribe to TensorFlow → https://goo.gle/TensorFlow