KGB Archiver console version ?005-2006 Tomasz Pawlak, tomekp17@gmail.com, mod by Slawek (poczta-sn@gazeta.pl) based on PAQ6 by Matt Mahoney PAQ6v2 - File archiver and compressor. (C) 2004, Matt Mahoney, mmahoney@cs.fit.edu This program is free softw
An object recognition system has been developed that uses a new class of local image features. The features are invariant to image scaling, translation, and rotation, and partially invariant to illumination changes and affine or 3D projection. These
Discovering knowledge from big multivariate data, recorded every days, requires specialized machine learning techniques. This book presents an easy to use practical guide in R to compute the most popular machine learning methods for exploring data s
Joel Grus ■■ Get a crash course in Python ■■ Learn the basics of linear algebra, statistics, and probability— and understand how and when they're used in data science ■■ Collect, explore, clean, munge, and manipulate data ■■ Dive into the fundamenta
1 Introduction and scope 2 Reasoning: goal trees and problem solving 3 Reasoning: goal trees and rule-based expert systems 4 Search: depth-first, hill climbing, beam 5 Search: optimal, branch and bound, A* 6 Search: games, minimax, and alpha-beta 7
k-Nearest Neighbors algorithm (k-NN) implemented on Apache Spark. This uses a hybrid spill tree approach to achieve high accuracy and search efficiency. The simplicity of k-NN and lack of tuning parameters makes k-NN a useful baseline model for many
This book is organized in two parts. Part I, The Fundamentals of Machine Learning, covers the following topics: What is Machine Learning? What problems does it try to solve? What are the main categories and fundamental concepts of Machine Learning s
Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamen
The flow capturing and the p-median location-allocation models deal quite differently with demand for service in a network. The p-median model assumes that demand is expressed at nodes and locates facilities to minimize the total distance between su
