Machine Learning and Data Mining: Lecture Notes

Small book cover: Machine Learning and Data Mining: Lecture Notes

Machine Learning and Data Mining: Lecture Notes

Publisher: University of Toronto
Number of pages: 134

Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; Monte Carlo Methods; Principal Components Analysis; Lagrange Multipliers; Clustering; Hidden Markov Models; Support Vector Machines; AdaBoost.

Home page url

Download or read it online for free here:
Download link
(1.6MB, PDF)

Similar books

Book cover: Understanding Machine Learning: From Theory to AlgorithmsUnderstanding Machine Learning: From Theory to Algorithms
by - Cambridge University Press
This book introduces machine learning and the algorithmic paradigms it offers. It provides a theoretical account of the fundamentals underlying machine learning and mathematical derivations that transform these principles into practical algorithms.
Book cover: Inductive Logic Programming: Theory and MethodsInductive Logic Programming: Theory and Methods
by - ScienceDirect
Inductive Logic Programming is a new discipline which investigates the inductive construction of first-order clausal theories from examples and background knowledge. The authors survey the most important theories and methods of this new field.
Book cover: Reinforcement LearningReinforcement Learning
by - InTech
This book describes and extends the scope of reinforcement learning. It also shows that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional controllers.
Book cover: Introduction to Machine LearningIntroduction to Machine Learning
by - Cambridge University Press
Over the past two decades Machine Learning has become one of the mainstays of information technology and a rather central part of our life. Smart data analysis will become even more pervasive as a necessary ingredient for technological progress.