A Concise Introduction to Machine Learning uses mathematics as the common language to explain a variety of machine learning concepts from basic principles, and illustrates every concept using examples in MATLAB.
A Concise Introduction to Machine Learning uses mathematics as the common language to explain a variety of machine learning concepts from basic principles, and illustrates every concept using examples in MATLAB.
A.C. Faul was a Teaching Associate, Fellow and Director of Studies in Mathematics at Selwyn College, University of Cambridge. She came to Cambridge after studying two years in Germany. She did Part II and Part III Mathematics at Churchill College, Cambridge. Since these are only two years, and three years are necessary for a first degree, she does not hold one. However, this was followed by a PhD on the Faul-Powell Algorithm for Radial Basis Function Interpolation under the supervision of Professor Mike Powell. She then worked on the Relevance Vector Machine with Mike Tipping at Microsoft Research Cambridge. Ten years in industry followed where she worked on various algorithms on mobile phone networks, image processing and data visualization. Current projects are on machine learning techniques. In teaching, she enjoys to bring out the underlying, connecting principles of algorithms, which is the emphasis of a book on Numerical Analysis she has written.
Inhaltsangabe
Chapter 1. Introduction Chapter 2. Probability Theory Chapter 3. Sampling Chapter 4. Linear Classification Chapter 5. Non-Linear Classification Chapter 6. Dimensionality Reduction Chapter 7. Regression Chapter 8. Feature Learning Appendix A. Matrix Formulae Index
