Mathematics For Machine Learning Marc Peter Deisenroth A Aldo Faisal Cheng Soon Ong Αγγλικά Βιβλία Science

The Fundamental Mathematical Tools Needed To Understand Machine Learning Include Linear Algebra Analytic Geometry Matrix Decompositions Vector Calculus Optimization Probability And Statistics These Topics Are Traditionally Taught In Disparate Courses Making It Hard For Data Science Or Computer Students Professionals Efficiently Learn Mathematics This Self-Contained Textbook Bridges Gap Between Texts Introducing Concepts With A Minimum Of Prerequisites Uses Derive Four Central Methods: Regression Principal Component Analysis Gaussian Mixture Models Support Machines Others Background Derivations Provide Starting Point Those First Time Methods Help Build Intuition Practical Experience Applying Every Chapter Includes Worked Examples Exercises Test Understanding Programming Tutorials Offered On Book\ S Web Site Έτος Έκδοσης: 2020 Διαστάσεις: 23 4X23 4Cm