**Learning Deep Architectures for AI**

by Yoshua Bengio

**Publisher**: Now Publishers 2009**ISBN/ASIN**: 1601982941**ISBN-13**: 9781601982940**Number of pages**: 130

**Description**:

This monograph discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.

Download or read it online for free here:

**Download link**

(1.1MB, PDF)

## Similar books

**Machine Learning for Designers**

by

**Patrick Hebron**-

**O'Reilly Media**

This book introduces you to contemporary machine learning systems and helps you integrate machine-learning capabilities into your user-facing designs. Patrick Hebron explains how machine-learning applications can affect the way you design websites.

(

**3527**views)

**Inductive Logic Programming: Theory and Methods**

by

**Stephen Muggleton, Luc de Raedt**-

**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.

(

**29301**views)

**Algorithms for Reinforcement Learning**

by

**Csaba Szepesvari**-

**Morgan and Claypool Publishers**

We focus on those algorithms of reinforcement learning that build on the theory of dynamic programming. We give a comprehensive catalog of learning problems, describe the core ideas, followed by the discussion of their properties and limitations.

(

**4919**views)

**Elements of Causal Inference: Foundations and Learning Algorithms**

by

**J. Peters, D. Janzing, B. Schölkopf**-

**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 ...

(

**2763**views)