Linear Algebra for Data Science & Machine Learning – Math

Course content

• Vectors Basics
• Vector Projections
• Basis of Vectors
• Matrix Basics from High school
• Matrices – Setting up the stage – Transformations
• Gaussian Elimination
• Einstein Summation convention – Non Orthogonal basis – Gram Schmidt Process
• Eigen Problems
• Principal Component Analysis – Application of Eigen Values and Eigen Vectors
• Google Pagerank Algorithm
• SVD – Singular Value Decomposition
• Pseudo Inverse
• Matrix Decompositions
• Solving the Linear Regression using Matrix Decomposition
• methods
• Linear Regression from Scratch
• Linear Algebra in Natural Language Processing
• Linear Algebra for Deep Learning – Getting started with Pytorch
• Linear Regression Using Pytorch
• Python Basics
• Python for Data Science
• Basics of Statistics
• Appendix : Python for Data Science
• Machine Learning for Projects