Algorithms

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

An accessible introduction to algorithms, explaining not just what they are but how they work, with examples from a wide range of application areas. Digital technology runs on algorithms, sets of instructions that describe how to do something efficiently. Application areas range from search engines to tournament scheduling, DNA sequencing, and machine learning. Arguing that every educated person today needs to have some understanding of algorithms and what they do, in this volume in the MIT Press Essential Knowledge series, Panos Louridas offers an introduction to algorithms that is accessible to the nonspecialist reader. Louridas explains not just what algorithms are but also how they work, offering a wide range of examples and keeping mathematics to a minimum. After discussing what an algorithm does and how its effectiveness can be measured, Louridas covers three of the most fundamental applications areas: graphs, which describe networks, from eighteenth-century problems to today's social networks; searching, and how to find the fastest way to search; and sorting, and the importance of choosing the best algorithm for particular tasks. He then presents larger-scale applications: PageRank, Google's founding algorithm; and neural networks and deep learning. Finally, Louridas describes how all algorithms are nothing more than simple moves with pen and paper, and how from such a humble foundation rise all their spectacular achievements.

Author(s): Panos Louridas
Series: The MIT Press Essential Knowledge series
Edition: 1
Publisher: The MIT Press
Year: 2020

Language: English
Commentary: Vector PDF
Pages: 312
City: Cambridge, MA
Tags: Algorithms; Deep Learning; Graph Algorithms; Search Algorithms; Sorting Algorithms; PageRank; Elementary

Contents
Series Foreword
Preface
Acknowledgments
1: What Is an Algorithm?
The Algorithmic Age
A Way to Do Things
Our First Algorithm
Algorithms, Computers, and Mathematics
Measuring Algorithms
Complexity Families
2: Graphs
From Graphs to Algorithms
Paths and DNA
Scheduling a Tournament
Shortest Paths
3: Searching
A Needle in a Haystack
The Matthew Effect and Search
Kepler, Cars, and Secretaries
Binary Search
4: Sorting
Simple Sorting Methods
Radix Sort
Quicksort
Merge Sort
5: PageRank
The Basic Principles
An Example
The Hyperlink Matrix and Power Method
Dangling Nodes and the Random Surfer
The Google Matrix
PageRank in Practice
6: Deep Learning
Neurons, Real and Artificial
The Learning Process
From Neurons to Neural Networks
The Backpropagation Algorithm
Recognizing Clothes
Getting to Deep Learning
Epilogue
Glossary
Notes
Preface
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Epilogue
References
Further Reading
Index