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In all of our discussions about how the digital revolution has created a system in which people donβt actually own the things they think theyβre buying, I get particularly frustrated byβ¦
SpaceX shares dipped below their IPO price of $135 on Wednesday morning for the first time since listing, signaling dwindling hype around the Elon Musk company.
This book is about the mathematical foundations of data science. 1. Introduction 2. Curses, Blessings, and Surprises in High Dimensions 3. Singular Value Decomposition and Principal Component Analysis 4. Linear Regression and Regularization 5. Graphs, Networks, and Clustering 6. Nonlinear Dimension Reduction and Diffusion Maps 7. Linear Dimension Reduction via Random Projections 8. Optimization for Data Science 9. Classification 10. A Mathematical Introduction to Deep Learning 11. Large Sample Limit of Graph Laplacians 12. Community 13. Concentration of Measure and Gaussian Analysis 14. Matrix Concentration Inequalities 15. Compressive Sensing and Sparsity 16. Low-Rank Matrix Recovery
The recent end-of-financial-year sales were rather interesting β I found myself spending a lot more time browsing AliExpress than I did Amazon or eBay this year which is something I wouldnβ¦