Logo

Introduction to Machine Learning

Small book cover: Introduction to Machine Learning

Introduction to Machine Learning
by

Publisher: arXiv
Number of pages: 109

Description:
Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).

Home page url

Download or read it online for free here:
Download link
(680KB, PDF)

Similar books

Book cover: Introduction to Machine Learning for the SciencesIntroduction to Machine Learning for the Sciences
by - arXiv.org
This is an introductory machine learning course specifically developed with STEM students in mind, written by the theoretical Condensed Matter Theory group at the University of Zurich. We discuss supervised, unsupervised, and reinforcement learning.
(3627 views)
Book cover: A Course in Machine LearningA Course in Machine Learning
by - ciml.info
Tis is a set of introductory materials that covers most major aspects of modern machine learning (supervised and unsupervised learning, large margin methods, probabilistic modeling, etc.). It's focus is on broad applications with a rigorous backbone.
(22721 views)
Book cover: An Introductory Study on Time Series Modeling and ForecastingAn Introductory Study on Time Series Modeling and Forecasting
by - arXiv
This work presents a concise description of some popular time series forecasting models used in practice, with their features. We describe three important classes of time series models, viz. the stochastic, neural networks and SVM based models.
(12518 views)
Book cover: Elements of Causal Inference: Foundations and Learning AlgorithmsElements of Causal Inference: Foundations and Learning Algorithms
by - The MIT Press
This book offers a self-contained and concise introduction to causal models and how to learn them from data. The book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from data ...
(6707 views)