Scattered notes of Machine Learning: A vademecum to understand one of the most fascinating topics of our time

Rodolfi, Luca

ISBN 10: 1672432898 / ISBN 13: 9781672432894

Published by Independently published, 2019

About this Item

220 pages. 9.25x7.50x0.52 inches. In Stock.

Seller Inventory # zk1672432898

Bibliographic Details

• Title: Scattered notes of Machine Learning: A vademecum to understand one of the most fascinating topics of our time
• Publisher: Independently published
• Publication Date: 2019
• Language: English
• ISBN 10: 1672432898
• ISBN 13: 9781672432894
• Binding: Paperback
• Condition: Brand New
• Weight: 0.49 kilograms

About this title

Synopsis

Every day I deal with technological issues related to the analysis and understanding of data, so I decided to collect and organize notes regarding Machine Learning, a topic that never than before seems to have taken off as a "tool" to further increase the competitiveness of the company.Obviously, the web is an endless source of information on such a contemporary subject and the risk of "getting lost" among too many information, sometimes too technical or too simplistic, is just around the corner.The following notes are designed for a specific target audience that includes:The curious, technology enthusiasts who want to have a clear description of the subject.Business people who do not have a technical background and who are not interested in knowing what is "under the hood" but that want to understand, with a good level of detail, features, functionality, examples of what is machine learning and why they should evaluate it to make more competitive their companies.Computer technicians who deal with "other things" and who want to have a description of the subject.This book will be for me an opportunity to describe some interesting (and in some ways fascinating) "cases" and some clever ideas to solve "problems" simply impossible until few years ago.The volume is divided into 4 independent parts:The first is an introduction to machine learning to explain what it is, what terminology and tools make up the basis, how it works from a process point of view.The second is the most useful for readers interested in the "value" that machine learning can provide: it contains concrete cases explaining how business can take advantage of using Machine Learning to speed up the go to market and to be more competitive.The third is a description of the main types and algorithms of machine learning, where can’t be avoided some technical details even if the type of explanation is always designed for a reader without any particular computer background.The last is an appendix with some examples of what's under the hood, nothing too complex (for that web resources are much more useful because they allow you to verify the code described directly in development environments with simple copy/paste), but useful to appreciate logic and implementation of some basic ideas.