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Author : John F. Magee
Publisher : Unknown
Page : 13 pages
File Size : 41,8 Mb
Release : 1964
Category : Business logistics
ISBN : OCLC:10898703
Author : Helen C. Abell Collection,John F. Magee,Helen C. Abell
Publisher : Unknown
Page : 26 pages
File Size : 50,9 Mb
Release : 1972
Category : Electronic
ISBN : OCLC:625908655
Author : Magee
Publisher : Unknown
Page : 128 pages
File Size : 46,9 Mb
Release : 1964-01-01
Category : Electronic
ISBN : 0000644102
Author : Christoph Molnar
Publisher : Lulu.com
Page : 320 pages
File Size : 40,9 Mb
Release : 2020
Category : Artificial intelligence
ISBN : 9780244768522
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Author : Patrick A. Ray,Casey M. Brown
Publisher : World Bank Publications
Page : 146 pages
File Size : 55,7 Mb
Release : 2015-08-20
Category : Business & Economics
ISBN : 9781464804786
Confronting Climate Uncertainty in Water Resources Planning and Project Design describes an approach to facing two fundamental and unavoidable issues brought about by climate change uncertainty in water resources planning and project design. The first is a risk assessment problem. The second relates to risk management. This book provides background on the risks relevant in water systems planning, the different approaches to scenario definition in water system planning, and an introduction to the decision-scaling methodology upon which the decision tree is based. The decision tree is described as a scientifically defensible, repeatable, direct and clear method for demonstrating the robustness of a project to climate change. While applicable to all water resources projects, it allocates effort to projects in a way that is consistent with their potential sensitivity to climate risk. The process was designed to be hierarchical, with different stages or phases of analysis triggered based on the findings of the previous phase. An application example is provided followed by a descriptions of some of the tools available for decision making under uncertainty and methods available for climate risk management. The tool was designed for the World Bank but can be applicable in other scenarios where similar challenges arise.
Author : Dr. Avinash S. Jagtap
Publisher : Lulu.com
Page : 314 pages
File Size : 51,8 Mb
Release : 2024-06-30
Category : Electronic
ISBN : 9780359354627
Author : Wayne W. Daniel
Publisher : Unknown
Page : 20 pages
File Size : 43,5 Mb
Release : 1979
Category : Decision making
ISBN : STANFORD:36105035885206
Author : Oleksandr Sosnovshchenko,Oleksandr Baiev
Publisher : Packt Publishing Ltd
Page : 371 pages
File Size : 45,5 Mb
Release : 2018-02-28
Category : Computers
ISBN : 9781787123526
Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease Key Features Implement effective machine learning solutions for your iOS applications Use Swift and Core ML to build and deploy popular machine learning models Develop neural networks for natural language processing and computer vision Book Description Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. What you will learn Learn rapid model prototyping with Python and Swift Deploy pre-trained models to iOS using Core ML Find hidden patterns in the data using unsupervised learning Get a deeper understanding of the clustering techniques Learn modern compact architectures of neural networks for iOS devices Train neural networks for image processing and natural language processing Who this book is for iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book.
Author : Dennis V. Lindley
Publisher : Unknown
Page : 232 pages
File Size : 53,7 Mb
Release : 1985-12-23
Category : Business & Economics
ISBN : UOM:39015016210174
Making Decisions Second Edition D.V. Lindley Formerly Professor of Statistics, University College London This book looks at the problems involved in decision-making and argues that there is only one logical way to make a decision. By the use of three basic principles--assigning probabilities to the uncertain events; assigning utilities to the possible consequences; and choosing that decision that maximizes expected utility--decisions can be reached more efficiently and with less disagreement. It shows that only maximization of expected utility leads to sensible decision-making. This extensively revised second edition uses only elementary mathematics and will be of interest to all those concerned with decision-making and its consequences. Since his retirement from University College London in 1977 Professor Lindley has held visiting appointments at Berkeley, University of Florida, George Washington University, University of Sao Paulo, University of Wisconsin, Monash University, Australia, and University of Canterbury, New Zealand. Contents * Decisions and uncertain events * A numerical measure for uncertainty * The laws of probability * A numerical measure for consequences * The utility of money * Bayes' Theorem * Value of information * Decision trees * The assessment of probabilities and utilities * An appreciation Appendix Answers to exercises Glossary of Symbols Subject Index
Author : Mark Koning,Chris Smith
Publisher : Independently Published
Page : 168 pages
File Size : 40,6 Mb
Release : 2017-10-04
Category : Computers
ISBN : 1549893750
If you want to learn how decision trees and random forests work, plus create your own, this visual book is for you. The fact is, decision tree and random forest algorithms are powerful and likely touch your life everyday. From online search to product development and credit scoring, both types of algorithms are at work behind the scenes in many modern applications and services. They are also used in countless industries such as medicine, manufacturing and finance to help companies make better decisions and reduce risk. Whether coded or scratched out by hand, both algorithms are powerful tools that can make a significant impact. This book is a visual introduction for beginners that unpacks the fundamentals of decision trees and random forests. If you want to dig into the basics with a visual twist plus create your own algorithms in Python, this book is for you.
Author : Stuart B. Mushlin,Harry L. Greene
Publisher : Elsevier Health Sciences
Page : 754 pages
File Size : 51,6 Mb
Release : 2009-10-27
Category : Medical
ISBN : 9780323041072
This popular reference facilitates diagnostic and therapeutic decision making for a wide range of common and often complex problems faced in outpatient and inpatient medicine. Comprehensive algorithmic decision trees guide you through more than 245 disorders organized by sign, symptom, problem, or laboratory abnormality. The brief text accompanying each algorithm explains the key steps of the decision making process, giving you the clear, clinical guidelines you need to successfully manage even your toughest cases. An algorithmic format makes it easy to apply the practical, decision-making approaches used by seasoned clinicians in daily practice. Comprehensive coverage of general and internal medicine helps you successfully diagnose and manage a full range of diseases and disorders related to women's health, emergency medicine, urology, behavioral medicine, pharmacology, and much more. A Table of Contents arranged by organ system helps you to quickly and easily zero in on the information you need. More than a dozen new topics focus on the key diseases and disorders encountered in daily practice. Fully updated decision trees guide you through the latest diagnostic and management guidelines.
Author : Christina H. Gladwin
Publisher : SAGE
Page : 112 pages
File Size : 46,9 Mb
Release : 1989-09
Category : Social Science
ISBN : 0803934874
Why do people in a certain group behave the way they do? And, more importantly, what specific criteria was used by the group in question? This book presents a method for answering these questions.
Author : Byron M. Roth,John D. Mullen
Publisher : Rowman & Littlefield
Page : 454 pages
File Size : 40,8 Mb
Release : 2002-07
Category : Education
ISBN : 0742512746
This text, written by a philosopher and a social psychologist, emphasizes concrete applications of decision research to problems of everyday living, as well as to business, social, and political issues. The text contains scores of interesting examples and problems for analysis, ranging from personal decisions about medical treatment to Truman's decision to use the atomic bomb. There is no other text with such a wide-ranging coverage, with so practical an orientation, with such clear descriptions of the steps to effective decision making, and with so many end-of-chapter problems for analysis and practice.
Author : Francis X. Govers
Publisher : Packt Publishing Ltd
Page : 336 pages
File Size : 45,9 Mb
Release : 2018-08-30
Category : Computers
ISBN : 9781788835701
Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book DescriptionArtificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence.What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot’s intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics.
Author : John Band,Lesley Partridge
Publisher : Select Knowledge Limited
Page : 156 pages
File Size : 55,6 Mb
Release : 1999
Category : Electronic
ISBN : 9780744627855
This title looks at decision making from the manager’s viewpoint and aims to help you to improve your decision making. It also recognises that, in business today, decision making is everyone’s responsibility. Decision making for staff, who are not managers, is often through involvement in team decisions and the module also explores the benefits and limitations of team decision making.
