Data science and analytics strategy, Awati, Kailash Scriven, Alexander (university Technology Of Sydney, Australia)
Автор: Guo, Xin , Lai, Tze Leung , Shek, Howard , Wong Название: Quantitative Trading ISBN: 0367871815 ISBN-13(EAN): 9780367871819 Издательство: Taylor&Francis Рейтинг: Цена: 10104.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part cove
Автор: Shinde, Gitanjali Rahul (department Of Computer Engineering, Stes`s, Smt. Kashibai Navale College Of Engineering, Pune, India) Kalamkar, Asmita Balasa Название: Data analytics for coronavirus disease (covid-19) outbreak ISBN: 0367558467 ISBN-13(EAN): 9780367558468 Издательство: Taylor&Francis Рейтинг: Цена: 9186.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The focus of this book is data analytics for COVID-19 which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussion on data models, their performance, different Big data techniques, tools and technologies.
Автор: Burk, Scott , Miner, Gary Название: It`s All Analytics! ISBN: 0367359685 ISBN-13(EAN): 9780367359683 Издательство: Taylor&Francis Рейтинг: Цена: 9492.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject.
Автор: Perros, Harry G. Название: An Introduction to IoT Analytics ISBN: 0367686317 ISBN-13(EAN): 9780367686314 Издательство: Taylor&Francis Рейтинг: Цена: 7808.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers techniques that can be used to analyze data from IoT sensors and also addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so that one can learn how to apply these tools in practice with a good understanding of their inner workings.
Автор: Skillicorn, David B. Название: Cyberspace, data analytics, and policing ISBN: 036764276X ISBN-13(EAN): 9780367642761 Издательство: Taylor&Francis Рейтинг: Цена: 10258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Cyberspace, Data Analytics, and Policing surveys the changes that cyberspace has brought to criminality and to policing with enough technical content to expose the issues and suggest ways in which law enforcement organizations can adapt.
Автор: Dwight Steward; Roberto Cavazos Название: Big Data Analytics in U.S. Courts ISBN: 303031779X ISBN-13(EAN): 9783030317799 Издательство: Springer Рейтинг: Цена: 6097.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This Palgrave Pivot identifies the key legal, economic, and policy issues surrounding the allowance to use and interpret electronic data consistently and in a scientifically valid manner in U.S. courts. Evidence based on the analysis of large amounts of electronic data ('Big Data') plays an increasing role in civil court disputes, providing information that could not have been obtained from a witness stand. While Big Data evidence presents opportunities, it also presents legal and public policy challenges and concerns. How can one be sure that deviations found in Big Data fall outside the norm? If statistical analyses can be conducted and presented different ways, how can judges and juries make sense of conflicting interpretations? When does Big Data extraction stop being investigative and instead become an invasion of privacy? This book traces the history of Big Data use in U.S. courts, couples current case studies with legal challenges to explore key controversies, and suggests how courts can change the way they handle Big Data to ensure that findings are statistically significant and scientifically sound.
Автор: Westland, J. Christopher Название: Audit analytics ISBN: 3030490904 ISBN-13(EAN): 9783030490904 Издательство: Springer Рейтинг: Цена: 9146.00 р. Наличие на складе: Нет в наличии.
Описание: Today, information technology plays a pivotal role in financial control and audit: most financial data is now digitally recorded and dispersed among servers, clouds and networks over which the audited firm has no control.
Автор: Green, Fiona Название: Winning with data in the business of sports ISBN: 0367610701 ISBN-13(EAN): 9780367610708 Издательство: Taylor&Francis Рейтинг: Цена: 4898.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This new edition of the bestselling book shares the processes and principles used to implement a data-driven approach to decision-making, targeted marketing, and digital transformation, emulating the approach of brands such as Netflix, Amazon and Spotify but framed for the unique challenges and opportunities of the sports industry.
Описание: Chapter 1: Industrial Internet of Things FrameworkLayered View of IIoT systemsAnalytics Capabilities in IIoT Systems Can Increase Job Satisfaction Examples of IIoT Business Models Power Distribution Systems in the IIoTIIoT in Process Control Alarm Management Power Generation Turbines Anomaly Detection Increase Share of Wallet of Industrial Services and Products Power Transformers and Utility Equipment Analysis Demand Forecast of Products and Spare Parts ReferencesChapter 2: Industrial AnalyticsMachine Learning Supervised Machine Learning Decision Trees for Classification and RegressionRandom Forest Classification and Regression Neural Networks for Classification and Regression Sentiment Analysis and Machine Learning Support Vector Machines Unsupervised Machine Learning Association Rule MiningK-Means Clustering Anomaly Detection Machine LearningAnalytic Conduits References Chapter 3: Machine Learning to Predict Fault Events in Power Distribution Systems Problem Statement Background Data for Forecasting Fault Events in Power Distribution Grids Forecasting Fault Events Creation of Machine Learning Models Zone Prediction ModelsSubstation Prediction ModelsInfrastructure Prediction ModelsFeeder Prediction ModelsProactive Fault Analytics Helps Improving the Business Model and Employee SatisfactionReferencesChapter 4: Analyzing Events and Alarms in Control Systems Problem StatementBackgroundAnatomy of Alarms in IIoT Distributed Control SystemsAlarm Data Alarm Management Analytics Models Sequence Pattern Mining and Association Rule MiningAlarm Baskets Alarm De-chattering AnalysisAlarm Sequence AnalysisMeasures of Significance or Metrics for Sequence AnalysisEnhancing Expert Knowledge of Plant Operations Through Advanced Analytics Alarm ManagementReferencesChapter 5: Condition Monitoring of Rotating Machines in Power Generation Plants Problem Statement BackgroundTurbine Telemetry DataAnalytics for Anomaly Detection of Rotating MachinesStatistical Analysis of Turbine DataClustering Analysis of Turbine DataAnomaly Detection Using Connectivity-based Outlier FactorEnhancing Domain Knowledge of Power Engineers Through Anomaly Detection SystemReferencesChapter 6: Machine Learning Recommender for New Products and Services Problem StatementBackgroundHistorical DataProduct and Services Recommender AnalyticsCustomer Classification AnalyticsMarket Basket AnalysisSentiment Analysis Enhancing Domain Knowledge of Service Engineer Salespeople Through the Product and Services Recommender System ReferencesChapter 7: Managing Analytic Projects in the IIoT Enterprise Definition Phases of an Analytics Project in the IIoT Enterprise Delivery Framework for IIoT Advanced Analytics ProjectsSustaining Phase Requirements Engineering Project Management Process Data Preparation Phase Analytics and Implementation Phase Technical Solution Process Verification and Validation Processes Agile Kanban Development Lifecycle Barrie
Автор: Wolfgang Karl H?rdle; Henry Horng-Shing Lu; Xiaoto Название: Handbook of Big Data Analytics ISBN: 3319182838 ISBN-13(EAN): 9783319182834 Издательство: Springer Рейтинг: Цена: 34150.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Автор: Argote Cusi Milenka Linneth, Parra Bernal Leуn Darнo Название: Global Entrepreneurship Analytics: Using GEM Data ISBN: 0367542099 ISBN-13(EAN): 9780367542092 Издательство: Taylor&Francis Рейтинг: Цена: 3673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This innovative book proposes new methodologies for the measurement of entrepreneurship by applying techniques of demography, engineering, mathematics and statistics. This book will be of value to students at an advanced level, academics, and researchers in the fields of Entrepreneurship, Business analytics and Research Methodology.
Автор: Wrembel Название: Big Data Analytics and Knowledge Discovery ISBN: 3031126696 ISBN-13(EAN): 9783031126697 Издательство: Springer Рейтинг: Цена: 8537.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume LNCS 13428 constitutes the papers of the 24 th International Conference on Big Data Analytics and Knowledge Discovery, held in August 2022 in Vienna, Austria. The 12 full papers presented together with 12 short papers in this volume were carefully reviewed and selected from a total of 57 submissions. The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.
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