AI Algorithms, Data Structures, and Idioms Part 1

Idioms, Patterns, and Programming Idioms and Patterns Design patterns capture and communicate a form of knowledge that is essential to creating computer programs that users will »

Learning scikit-learn

Preface Any machine learning problem can be represented with the following three concepts: We will have to learn to solve a task T. We will need »

Deep Learning Part I Applied Math and Machine Learning Basics2

Probability and Information Theory Probability theory is a mathematical framework for representing uncertain statements. In AI we use probability theory in two major ways. First, the »

Deep Learning Chapter 1 Introduction

The many Names and Changing Fortunes of Neural Networks The earliest predecessors of modern deep learning were simple linear models motivated from a neuroscientific perspective. The »

Deep Learning Part I Applied Math and Machine Learning Basics 1

We begin with general ideas from applied math. Next, we describe the fundamental goals of machine learning. This elementary framework is the basis for a broad »