Machine Learning for Financial Engineering

隨著金融市場高度電子化，交易方式與競爭邏輯快速改變。本書從全球證券與衍生性商品市場出發，系統性說明電子交易的核心模式、基礎建設與法規環境。作者以清楚的結構，帶領讀者理解專業電子交易者如何在不同平台中運作與獲利，並分析技術革新對市場效率與風險管理的影響。作為 Wiley Trading 系列之一，本書聚焦產業第一線的實際需求，適合作為專業人士的參考工具，也能協助讀者建立對電子金融市場的整體認識。This book tackles the concepts, technical architecture, recent developments, and future opportunities in the new field of "direct access" electronic markets. The author provides a comprehensive coverage of electronic market models, exchange platforms and networks, while describing ways in which professional electronic traders make money. Professional Electronic Trading is one of the few books that deals directly with the issues that industry professionals confront every day, making it an ideal reference and training tool. David James Norman (Chicago, IL) is Director of Electronic Markets Development at the Center for Law and Financial Markets at IIT. New technology and the advent of electronic trading have opened the floodgates to both foreign and domestic markets. Traders need the wisdom of

本套 Volume 2 音檔 CD 專為《Open for Business》第二冊設計，提供學習者與母語者同步聆聽、反覆跟讀的練習機會。音檔內容完整對應課文段落、句型示例與重點詞彙解析，協助強化聽力理解與口語表達。全系列鎖定大學三、四年級程度，結合進階華語訓練與當代商業議題，涵蓋中國的產業發展、管理實務與經濟趨勢。完成一年課程後，學習者可閱讀商業期刊、理解專業文件，並以中文進行簡報與商務溝通。本套音檔是深化學習成效、培養實用商業中文能力的重要輔助資源。The Open for Business, Volume 2 set of three audio CDs offers learners the opportunity to listen and repeat after a native speaker. This set contains audio recordings that correspond to Volume 2’s text sections, sentence structure examples, and vocabulary analyses.About the SeriesDesigned for students in the third or fourth year of a college-level Chinese language curriculum, Open for Business combines language learning with an introduction to business trends and issues such as macroeconomics, technological innovations, modern management practices, and much more. Upon completion of this one-year course, students will be able to read Chinese-language periodicals and business-related documents, as well as conduct business negotiations and presentations in Chinese

《Your Next Fifty Years》為現代中壯年重新定義「退休」的概念。作者 Collins 與 Wall 以心理學與理財專業為基礎，主張退休不該被視為結束，而是一場「再出發」──一段重新聚焦與實踐理想的時光。本書提供具體的思考方向與工具，如假期式退休、彈性工時與階段性退休等新選項，並附有表格、檢核表與「Smart Tips」協助規劃投資、保險與遺產安排。書中也關注女性與中年族群在職場變動、伴侶離世或健康挑戰下的財務應對，兼具實用與啟發性。For millions of Americans in their thirties and forties retirement will have an entirely different meaning than it had for their parents. Most have saved a little, spent a lot, seen pensions cut and Social Security squeezed, and will live longer than any generation before. Your Next Fifty Years challenges baby boomers to develop a completely new perspective: retirement as renaissance - not the end of working life, but rather a time to renew, refocus, and recharge, based on long-range dreams and goals. Collins and Wall draw upon their unique training in psychology and financial planning to explore practical alternatives to the traditional concept of retirementalternatives such as sabbaticals, flextime, and temporary or part-time retirement. With the help of worksh

The basic thesis of the work is that environmental problems are only to be solved by people - people who will be required to make value judgements in conflicts that go beyond narrowly conceived human concerns. Thus people require not only an ethical system, but a way of conceiving the world and themselves such that the intrinsic value of life and nature is obvious, a system based on 'deep ecological principles'. The book encourages readers to identify their own series of such parameters - their own ecosophies. Ecology, Comunity and Lifestyle will appeal to philosophers, specialists working on environmental issues, and the more general reader who is interested in learning some of the foundational ideas of the rapidly expanding field of environmental philosophy.

Dive into the fascinating world of science with the "Horrible Science" collection by Nick Arnold, a thrilling series that blends humor, curiosity, and educational insights to make learning an unforgettable adventure. This captivating 10-book set invites young readers to explore the weird, wacky, and sometimes downright disgusting aspects of the natural world, uncovering the secrets behind everything from microscopic monsters to shocking electricity.Titles in this Set:The Terrible TruthPainful PoisonAngry AnimalEvolve or DieUgly BugFatal ForcesShocking ElectricityMicroscopic MonsterSounds DreadfulKiller EnergyDescription In "The Terrible Truth," readers will discover the science behind some of the most gruesome historical events, while "Painful Poison" delves into the deadly substances lurking in nature and their surprising uses. "Angry Animals" introduces the wild side of the animal kingdom, exploring the bizarre behaviors and survival tactics of creatures big and small.Prepare to witn

Siblings Fritz and Franny have fun trying all the rides at the amusement park in this early reader from Geisel Honor winner Tina Kugler!Pick a Book. Grow a Reader!This series is part of Scholastic's early reader line, Acorn, aimed at children who are learning to read. With easy-to-read text, a short-story format, plenty of humor, and full-color artwork on every page, these books will boost reading confidence and fluency. Acorn books plant a love of reading and help readers grow!Get ready to ride! Fox siblings Fritz and Franny -- and their faithful dog, Fred -- are spending the day at the amusement park. After sizing up the tallest, fastest, and loudest rides they can find, these foxes come together on the perfect coaster. Geisel Honor winner Tina Kugler's easy-to-read text and humor-filled, full-color artwork will have young readers everywhere laughing out loud!

Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several modalities of data, from sequences of clicks to text, images, and social interactions. This book introduces common principles and methods that underpin the design of personalized predictive models for a variety of settings and modalities. The book begins by revising 'traditional' machine learning models, focusing on adapting them to settings involving user data, then presents techniques based on advanced principles such as matrix factorization, deep learning, and generative modeling, and concludes with a detailed study of the consequences and risks of deploying personalized predictive systems. A series of case studies in domains ranging from e-commerce to health plus hands-on projects and code examples will give readers understanding and experience with large-scale real-world datasets and the ability to design mod

This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.

This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.

Know how to adapt quantum computing and machine learning algorithms. This book takes you on a journey into hands-on quantum machine learning (QML) through various options available in industry and res

A concise overview of machine learning--computer programs that learn from data--the basis of such applications as voice recognition and driverless cars.Today, machine learning underlies a range of app

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure.Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value.

Based on interdisciplinary research into 'Directional Change', a new data-driven approach to financial data analysis, this book applies machine learning to financial market monitoring and algorithmic

This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for

This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for

Deep learning is revolutionizing how machine translation systems are built today. This book introduces the challenge of machine translation and evaluation - including historical, linguistic, and applied context -- then develops the core deep learning methods used for natural language applications. Code examples in Python give readers a hands-on blueprint for understanding and implementing their own machine translation systems. The book also provides extensive coverage of machine learning tricks, issues involved in handling various forms of data, model enhancements, and current challenges and methods for analysis and visualization. Summaries of the current research in the field make this a state-of-the-art textbook for undergraduate and graduate classes, as well as an essential reference for researchers and developers interested in other applications of neural methods in the broader field of human language processing.

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.

Machine Learning with Spark and Python Essential Techniques for Predictive Analytics Second Edition simplifies ML for practical uses by focusing on two key algorithms. This new second edition improves

This book covers machine learning, one of the hottest topics in more recent years. With computing power increasing exponentially and costs decreasing at the same time, there is no better time for mach

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investmentBig Data and Machine Learning in Quantitative Investment is not just about demonstrat

Harness the power of MATLAB to resolve a wide range of machine learning challenges. This book provides a series of examples of technologies critical to machine learning. Each example solves a real-wor

This book provides a unique, in-depth discussion of multiview learning, one of the fastest developing branches in machine learning. Multiview Learning has been proved to have good theoretical underpin

Create AI applications in Python and lay the foundations for your career in data scienceKey FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail wit

Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools

3 comprehensive manuscripts in 1 bookMachine Learning: An Essential Guide to Machine Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data and More

Pragmatic AI is the first truly practical guide to solving real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Writing for business professional

This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning technique

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different ap

Machine learning can be a difficult subject if you’re not familiar with the basics. With this book, you'll get a solid foundation of introductory principles used in machine learning with the sta

Become a machine learning pro! Google TensorFlow has become the darling of financial firms and research organizations, but the technology can be intimidating and the learning curve is steep. Luc

This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior.

This book summarizes recent advances in applying saddlepoint approximation methods to financial engineering. It addresses pricing exotic financial derivatives and calculating risk contributions to Val

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.Key FeaturesExplore machine learning techniques with prominent ope

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosyste

This book provides over 1,000 review questions and answers for all types of mechanical engineering exams. It covers all the aspects of mechanical engineering topics including thermodynamics, machine d

Illustrates how R may be used successfully to solve problems in quantitative financeApplied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset

Key FeaturesSecond edition of the bestselling book on Machine LearningA practical approach to key frameworks in data science, machine learning, and deep learningUse the most powerful Python libraries

This authoritative, expanded and updated second edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the

In Practical Machine Learning with H2O.ai, author Darren Cook introduces readers to H2O, an open-source machine learning package that is gaining popularity in the data science community. This concise