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Optimization In Action
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Book Synopsis Bayesian Optimization in Action by : Quan Nguyen
Download or read book Bayesian Optimization in Action written by Quan Nguyen and published by Simon and Schuster. This book was released on 2023-11-14 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Optimization in Action teaches you how to build Bayesian Optimisation systems from the ground up. This book transforms state-of-the-art research into usable techniques you can easily put into practice. With a range of illustrations, and concrete examples, this book proves that Bayesian Optimisation doesn't have to be difficult!
Book Synopsis Global Optimization in Action by : János D. Pintér
Download or read book Global Optimization in Action written by János D. Pintér and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: In science, engineering and economics, decision problems are frequently modelled by optimizing the value of a (primary) objective function under stated feasibility constraints. In many cases of practical relevance, the optimization problem structure does not warrant the global optimality of local solutions; hence, it is natural to search for the globally best solution(s). Global Optimization in Action provides a comprehensive discussion of adaptive partition strategies to solve global optimization problems under very general structural requirements. A unified approach to numerous known algorithms makes possible straightforward generalizations and extensions, leading to efficient computer-based implementations. A considerable part of the book is devoted to applications, including some generic problems from numerical analysis, and several case studies in environmental systems analysis and management. The book is essentially self-contained and is based on the author's research, in cooperation (on applications) with a number of colleagues. Audience: Professors, students, researchers and other professionals in the fields of operations research, management science, industrial and applied mathematics, computer science, engineering, economics and the environmental sciences.
Book Synopsis Bayesian Optimization in Action by : Quan Nguyen
Download or read book Bayesian Optimization in Action written by Quan Nguyen and published by Simon and Schuster. This book was released on 2024-01-09 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian optimization helps pinpoint the best configuration for your machine learning models with speed and accuracy. Put its advanced techniques into practice with this hands-on guide. In Bayesian Optimization in Action you will learn how to: Train Gaussian processes on both sparse and large data sets Combine Gaussian processes with deep neural networks to make them flexible and expressive Find the most successful strategies for hyperparameter tuning Navigate a search space and identify high-performing regions Apply Bayesian optimization to cost-constrained, multi-objective, and preference optimization Implement Bayesian optimization with PyTorch, GPyTorch, and BoTorch Bayesian Optimization in Action shows you how to optimize hyperparameter tuning, A/B testing, and other aspects of the machine learning process by applying cutting-edge Bayesian techniques. Using clear language, illustrations, and concrete examples, this book proves that Bayesian optimization doesn’t have to be difficult! You’ll get in-depth insights into how Bayesian optimization works and learn how to implement it with cutting-edge Python libraries. The book’s easy-to-reuse code samples let you hit the ground running by plugging them straight into your own projects. Forewords by Luis Serrano and David Sweet. About the technology In machine learning, optimization is about achieving the best predictions—shortest delivery routes, perfect price points, most accurate recommendations—in the fewest number of steps. Bayesian optimization uses the mathematics of probability to fine-tune ML functions, algorithms, and hyperparameters efficiently when traditional methods are too slow or expensive. About the book Bayesian Optimization in Action teaches you how to create efficient machine learning processes using a Bayesian approach. In it, you’ll explore practical techniques for training large datasets, hyperparameter tuning, and navigating complex search spaces. This interesting book includes engaging illustrations and fun examples like perfecting coffee sweetness, predicting weather, and even debunking psychic claims. You’ll learn how to navigate multi-objective scenarios, account for decision costs, and tackle pairwise comparisons. What's inside Gaussian processes for sparse and large datasets Strategies for hyperparameter tuning Identify high-performing regions Examples in PyTorch, GPyTorch, and BoTorch About the reader For machine learning practitioners who are confident in math and statistics. About the author Quan Nguyen is a research assistant at Washington University in St. Louis. He writes for the Python Software Foundation and has authored several books on Python programming. Table of Contents 1 Introduction to Bayesian optimization 2 Gaussian processes as distributions over functions 3 Customizing a Gaussian process with the mean and covariance functions 4 Refining the best result with improvement-based policies 5 Exploring the search space with bandit-style policies 6 Leveraging information theory with entropy-based policies 7 Maximizing throughput with batch optimization 8 Satisfying extra constraints with constrained optimization 9 Balancing utility and cost with multifidelity optimization 10 Learning from pairwise comparisons with preference optimization 11 Optimizing multiple objectives at the same time 12 Scaling Gaussian processes to large datasets 13 Combining Gaussian processes with neural networks
Author :Conference on Optimization in Action (1975 : University of Bristol) Publisher : ISBN 13 : Total Pages : pages Book Rating :4.:/5 (959 download)
Book Synopsis Optimization in Action : Proceedings of the Conference on Optimization in Action Held at the University of Bristol in January by : Conference on Optimization in Action (1975 : University of Bristol)
Download or read book Optimization in Action : Proceedings of the Conference on Optimization in Action Held at the University of Bristol in January written by Conference on Optimization in Action (1975 : University of Bristol) and published by . This book was released on 1976 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimization in Action by : Institute of Mathematics and Its Applications
Download or read book Optimization in Action written by Institute of Mathematics and Its Applications and published by . This book was released on 1976 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: A survey of methods for minimizing sums of squares of nonlinear; Smoothed non-functional interpretations of statistical and experimental data; Parameterization of nonlinear least square fitting problems; Use of optimization techniques in optical filter design; An application of optimization techniques to the design of an optical filter; Least squares fitting of mcconologue arcs; A view of unconstrained optimization; Optimization of frequency selective electrical networks; The choice of design parameters for overhead line vibration dampers.
Book Synopsis Undoing Optimization by : Alison B Powell
Download or read book Undoing Optimization written by Alison B Powell and published by Yale University Press. This book was released on 2021-04-13 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique examination of the civic use, regulation, and politics of communication and data technologies City life has been reconfigured by our use—and our expectations—of communication, data, and sensing technologies. This book examines the civic use, regulation, and politics of these technologies, looking at how governments, planners, citizens, and activists expect them to enhance life in the city. Alison Powell argues that the de facto forms of citizenship that emerge in relation to these technologies represent sites of contention over how governance and civic power should operate. These become more significant in an increasingly urbanized and polarized world facing new struggles over local participation and engagement. The author moves past the usual discussion of top-down versus bottom-up civic action and instead explains how citizenship shifts in response to technological change and particularly in response to issues related to pervasive sensing, big data, and surveillance in "smart cities".
Book Synopsis Landing Page Optimization by : Tim Ash
Download or read book Landing Page Optimization written by Tim Ash and published by John Wiley & Sons. This book was released on 2012-03-29 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fully updated guide to making your landing pages profitable Effective Internet marketing requires that you test and optimize your landing pages to maximize exposure and conversion rate. This second edition of a bestselling guide to landing page optimization includes case studies with before-and-after results as well as new information on web site usability. It covers how to prepare all types of content for testing, how to interpret results, recognize the seven common design mistakes, and much more. Included is a gift card for Google AdWords. Features fully updated information and case studies on landing page optimization Shows how to use Google's Website Optimizer tool, what to test and how to prepare your site for testing, the pros and cons of different test strategies, how to interpret results, and common site design mistakes Provides a step-by-step implementation plan and advice on getting support and resources Landing Page Optimization, Second Edition is a comprehensive guide to increasing conversions and improving profits.
Download or read book Optimize written by Lee Odden and published by John Wiley & Sons. This book was released on 2012-04-17 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Attract, engage, and inspire your customers with an "Optimize and Socialize" content marketing strategy Optimize is designed to give readers a practical approach to integrating search and social media optimization with content marketing to boost relevance, visibility, and customer engagement. Companies, large and small, will benefit from the practical planning and creative content marketing tactics in this book that have been proven to increase online performance across marketing, public relations, and customer service. Learn to incorporate essential content optimization and social media engagement principles thereby increasing their ability to acquire and engage relevant customers online. Optimize provides insights from Lee Odden, one of the leading authorities on Content and Online Marketing. This book explains how to: Create a blueprint for integrated search, social media and content marketing strategy Determine which creative tactics will provide the best results for your company Implement search and social optimization holistically in the organization Measure the business value of optimized and socialized content marketing Develop guidelines, processes and training to scale online marketing success Optimize offers a tested approach for a customer-centric and adaptive online marketing strategy that incorporates the best of content, social media marketing, and search engine optimization tactics.
Book Synopsis Web Performance in Action by : Jeremy Wagner
Download or read book Web Performance in Action written by Jeremy Wagner and published by Manning. This book was released on 2017-01-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Web Performance in Action is your companion guide to making websites faster. You'll learn techniques that speed the delivery of your site's assets to the user, increase rendering speed, decrease the overall footprint of your site, as well as how to build a workflow that automates common optimization techniques. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Nifty features, hip design, and clever marketing are great, but your website will flop if visitors think it's slow. Network conditions can be unpredictable, and with today's sites being bigger than ever, you need to set yourself apart from the competition by focusing on speed. Achieving a high level of performance is a combination of front-end architecture choices, best practices, and some clever sleight-of-hand. This book will demystify all these topics for you. About the Book Web Performance in Action is your guide to making fast websites. Packed with "Aha!" moments and critical details, this book teaches you how to create performant websites the right way. You'll master optimal rendering techniques, tips for decreasing your site's footprint, and technologies like HTTP/2 that take your website's speed from merely adequate to seriously fast. Along the way, you'll learn how to create an automated workflow to accomplish common optimization tasks and speed up development in the process. What's Inside Foolproof performance-boosting techniques Optimizing images and fonts HTTP/2 and how it affects your optimization workflow About the Reader This book assumes that you're familiar with HTML, CSS, and JavaScript. Many examples make use of Git and Node.js. About the Author Jeremy Wagner is a professional front-end web developer with over ten years of experience. Foreword by Ethan Marcotte. Table of Contents Understanding web performance Using assessment tools Optimizing CSS Understanding critical CSS Making images responsive Going further with images Faster fonts Keeping JavaScript lean and fast Boosting performance with service workers Fine-tuning asset delivery Looking to the future with HTTP/2 Automating optimization with gulp
Book Synopsis Dynamic Optimization by : Karl Hinderer
Download or read book Dynamic Optimization written by Karl Hinderer and published by Springer. This book was released on 2017-01-12 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.
Download or read book Website Optimization written by Rich Page and published by John Wiley & Sons. This book was released on 2012-04-23 with total page 593 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step instructions for executing a website testing and optimization plan Website optimization is can be an overwhelming endeavor due to the fact that it encompasses so many strategic and technical issues. However, this hands-on, task-based book demystifies this potentially intimidating topic by offering smart, practical, and tested instructions for developing, implementing, managing, and tracking website optimization efforts. After you learn how to establish an optimization framework, you then dive into learning how to develop a plan, test appropriately and accurately, interpret the results, and optimize in order to maximize conversion rates and improve profits. Zeroes in on fundamentals such as understanding key metrics, choosing analytics tools, researching visitors and their onsite behavior, and crafting a plan for what to test and optimize Walks you through testing and optimizing specific web pages including the homepage, entry and exit pages, product and pricing pages, as well as the shopping cart and check-out process Guides you through important optimization areas such as optimizing text and images Addresses advanced topics including paid search optimization, Facebook fan page optimization, rich media, and more Includes a companion website that features expanded examples, additional resources, tool reviews, and other related information Full of interesting case studies and helpful examples drawn from the author's own experience, Website Optimization: An Hour a Day is the complete solution for anyone who wants to get the best possible results from their web page.
Book Synopsis Patterns, Predictions, and Actions: Foundations of Machine Learning by : Moritz Hardt
Download or read book Patterns, Predictions, and Actions: Foundations of Machine Learning written by Moritz Hardt and published by Princeton University Press. This book was released on 2022-08-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impacts Patterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable perspective on its history and social implications. Beginning with the foundations of decision making, Moritz Hardt and Benjamin Recht explain how representation, optimization, and generalization are the constituents of supervised learning. They go on to provide self-contained discussions of causality, the practice of causal inference, sequential decision making, and reinforcement learning, equipping readers with the concepts and tools they need to assess the consequences that may arise from acting on statistical decisions. Provides a modern introduction to machine learning, showing how data patterns support predictions and consequential actions Pays special attention to societal impacts and fairness in decision making Traces the development of machine learning from its origins to today Features a novel chapter on machine learning benchmarks and datasets Invites readers from all backgrounds, requiring some experience with probability, calculus, and linear algebra An essential textbook for students and a guide for researchers
Book Synopsis Advances in Learning Automata and Intelligent Optimization by : Javidan Kazemi Kordestani
Download or read book Advances in Learning Automata and Intelligent Optimization written by Javidan Kazemi Kordestani and published by Springer Nature. This book was released on 2021-06-23 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA's application in behavior control in evolutionary computation, and memetic models of object migration automata and cellular learning automata for solving NP hard problems are considered. Next, an overview of multi-population methods for DOPs, LA's application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed. Highlighted benefits • Presents the latest advances in learning automata-based optimization approaches. • Addresses the memetic models of learning automata for solving NP-hard problems. • Discusses the application of learning automata for behavior control in evolutionary computation in detail. • Gives the fundamental principles and analyses of the different concepts associated with multi-population methods for dynamic optimization problems.
Book Synopsis Website Optimization by : Andrew B. King
Download or read book Website Optimization written by Andrew B. King and published by "O'Reilly Media, Inc.". This book was released on 2008-07-08 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remember when an optimized website was one that merely didn't take all day to appear? Times have changed. Today, website optimization can spell the difference between enterprise success and failure, and it takes a lot more know-how to achieve success. This book is a comprehensive guide to the tips, techniques, secrets, standards, and methods of website optimization. From increasing site traffic to maximizing leads, from revving up responsiveness to increasing navigability, from prospect retention to closing more sales, the world of 21st century website optimization is explored, exemplified and explained. Website Optimization combines the disciplines of online marketing and site performance tuning to attain the competitive advantage necessary on today's Web. You'll learn how to improve your online marketing with effective paid and natural search engine visibility strategies, strengthened lead creation and conversion to sales methods, and gold-standard ad copywriting guidelines. Plus, your increased site speed, reduced download footprint, improved reliability, and improved navigability will work synergistically with those marketing methods to optimize your site's total effectiveness. In this book for business and IT managers, author Andrew King, president of Website Optimization, LLC, has assembled experts in several key specialties to teach you: Search engine optimization -- addressing best (and worst) practices to improve search engine visibility, including step-by-step keyword optimization guidelines, category and tag cloud creation, and guerilla PR techniques to boost inbound links and improve rankings Pay-per-click optimization -- including ad copywriting guidelines, setting profit-driven goals, calculating and optimizing bids, landing page optimization, and campaign management tips Optimizing conversion rates -- increasing leads with site landing page guidelines, such as benefit-oriented copy, credibility-based design, value hierarchies, and tips on creating unique selling propositions and slogans Web performance tuning -- optimizing ways to use (X)HTML, CSS, and Ajax to increase speed, reduce your download footprint, and increase reliability Advanced tuning -- including client-side techniques such as on-demand content, progressive enhancement, and inline images to save HTTP requests. Plus server-side tips include improving parallelism, using cache control, browser sniffing, HTTP compression, and URL rewriting to remap links and preserve traffic Web metrics -- illustrating the best metrics and tools to gather details about visitors and measure web conversion and success rates. Covering both search marketing metrics and web performance measures including Pathloss and waterfall graphs Website Optimization not only provides you with a strategy for success, it also offers specific techniques for you and your staff to follow. A profitable website needs to be well designed, current, highly responsive, and optimally persuasive if you're to attract prospects, convert them to buyers, and get them to come back for more. This book describes precisely what you need to accomplish to achieve all of those goals.
Book Synopsis Automated Machine Learning in Action by : Qingquan Song
Download or read book Automated Machine Learning in Action written by Qingquan Song and published by Simon and Schuster. This book was released on 2022-06-07 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automated Machine Learning in Action reveals how you can automate the burdensome elements of designing and tuning your machine learning systems. --
Book Synopsis Encyclopedia of Business Analytics and Optimization by : Wang, John
Download or read book Encyclopedia of Business Analytics and Optimization written by Wang, John and published by IGI Global. This book was released on 2014-02-28 with total page 2754 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.
Book Synopsis Experimentation for Engineers by : David Sweet
Download or read book Experimentation for Engineers written by David Sweet and published by Simon and Schuster. This book was released on 2023-03-21 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimize the performance of your systems with practical experiments used by engineers in the world’s most competitive industries. In Experimentation for Engineers: From A/B testing to Bayesian optimization you will learn how to: Design, run, and analyze an A/B test Break the "feedback loops" caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization Clearly define business metrics used for decision-making Identify and avoid the common pitfalls of experimentation Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox of techniques for evaluating new features and fine-tuning parameters. You’ll start with a deep dive into methods like A/B testing, and then graduate to advanced techniques used to measure performance in industries such as finance and social media. Learn how to evaluate the changes you make to your system and ensure that your testing doesn’t undermine revenue or other business metrics. By the time you’re done, you’ll be able to seamlessly deploy experiments in production while avoiding common pitfalls. About the technology Does my software really work? Did my changes make things better or worse? Should I trade features for performance? Experimentation is the only way to answer questions like these. This unique book reveals sophisticated experimentation practices developed and proven in the world’s most competitive industries that will help you enhance machine learning systems, software applications, and quantitative trading solutions. About the book Experimentation for Engineers: From A/B testing to Bayesian optimization delivers a toolbox of processes for optimizing software systems. You’ll start by learning the limits of A/B testing, and then graduate to advanced experimentation strategies that take advantage of machine learning and probabilistic methods. The skills you’ll master in this practical guide will help you minimize the costs of experimentation and quickly reveal which approaches and features deliver the best business results. What's inside Design, run, and analyze an A/B test Break the “feedback loops” caused by periodic retraining of ML models Increase experimentation rate with multi-armed bandits Tune multiple parameters experimentally with Bayesian optimization About the reader For ML and software engineers looking to extract the most value from their systems. Examples in Python and NumPy. About the author David Sweet has worked as a quantitative trader at GETCO and a machine learning engineer at Instagram. He teaches in the AI and Data Science master's programs at Yeshiva University. Table of Contents 1 Optimizing systems by experiment 2 A/B testing: Evaluating a modification to your system 3 Multi-armed bandits: Maximizing business metrics while experimenting 4 Response surface methodology: Optimizing continuous parameters 5 Contextual bandits: Making targeted decisions 6 Bayesian optimization: Automating experimental optimization 7 Managing business metrics 8 Practical considerations
