**A First Encounter with Machine Learning**

by Max Welling

**Publisher**: University of California Irvine 2011**Number of pages**: 93

**Description**:

The book you see before you is meant for those starting out in the field of machine learning, who need a simple, intuitive explanation of some of the most useful algorithms that our field has to offer. A first read to wet the appetite so to speak, a prelude to the more technical and advanced text books.

Download or read it online for free here:

**Download link**

(420KB, PDF)

## Similar books

**Learning Deep Architectures for AI**

by

**Yoshua Bengio**-

**Now Publishers**

This book discusses the principles of 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.

(

**2805**views)

**Statistical Learning and Sequential Prediction**

by

**Alexander Rakhlin, Karthik Sridharan**-

**University of Pennsylvania**

This text focuses on theoretical aspects of Statistical Learning and Sequential Prediction. The minimax approach, which we emphasize throughout the course, offers a systematic way of comparing learning problems. We will discuss learning algorithms...

(

**2096**views)

**A Brief Introduction to Machine Learning for Engineers**

by

**Osvaldo Simeone**-

**arXiv.org**

This monograph provides the starting point to the literature that every engineer new to machine learning needs. It offers a basic and compact reference that describes key ideas and principles in simple terms and within a unified treatment.

(

**1024**views)

**Machine Learning and Data Mining: Lecture Notes**

by

**Aaron Hertzmann**-

**University of Toronto**

Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; and more.

(

**4663**views)