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AI and the future of banking
Across its entire breadth and depth, the banking industry is at the forefront of investigating Advanced Analytics and AI technology for use in a broad range of applications, such as customer analytics and providing wealth advice for clients. AI and the Future of Banking provides new and established banking industry professionals with the essential information on the implications of data and analytics on their roles, responsibilities and personal career development.
Advances in web mining and web usage analysis ; 6th International workshop on knowledge discovery on the web, WEBKDD 2004, Seattle, WA, USA, August 22-25, 2004, Revised Selected Papers
The Webisaliveenvironmentthatmanagesanddrivesawidespectrumofapp- cations in which a user may interact with a company, a governmental authority, a non-governmental organization or other non-pro?t institution or other users. User preferences and expectations, together with usage patterns, form the basis for personalized, user-friendly and business-optimal services. Key Web business metrics enabled by proper data capture and processing are essential to run an e?ective business or service. Enabling technologies include data mining, sc- able warehousing and preprocessing, sequence discovery, real time processing, document classi?cation, user modeling and quality evaluation models for them. Recipient technologies required for user pro?ling and usage patterns include recommendation systems, Web analytics applications, and application servers, coupled with content management systems and fraud detectors.
Advances in Medical Engineering
In this book, research and development trends of physics, engineering, mathematics and computer sciences in biomedical engineering are presented. Contributions from industry, clinics, universities and research labs with foci on medical imaging (CT, MRT, US, PET, SPECT etc.), medical image processing (segmentation, registration, visualization etc.), computer-assisted surgery (medical robotics, navigation), biomechanics (motion analysis, accident research, computer in sports, ergonomics etc.), biomedical optics (OCT, soft-tissue optics, optical monitoring etc.) and laser medicine (tissue ablation, gas analytics, topometry etc.) give insight to recent engineering, clinical and mathematical studies.
Advances in Big Data Analytics : Theory, Algorithms and Practices
Provides a comprehensive and cutting-edge study on big data analytics, based on the research findings and applications developed by the author and his colleagues in related areas. It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. The book also explores lessons learned in applying big data to business, engineering and healthcare. Lastly, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence.
Advanced REIT Portfolio Optimization : Innovative Tools for Risk Management
This book provides an investor-friendly presentation of the premises and applications of the quantitative finance models governing investment in one asset class of publicly traded stocks, specifically real estate investment trusts (REITs). The models provide highly advanced analytics for REIT investment, including: portfolio optimization using both historic and predictive return estimation; model backtesting; a complete spectrum of risk assessment and management tools with an emphasis on early warning systems, risk budgeting, estimating tail risk, and factor analysis; derivative valuation; and incorporating ESG ratings into REIT investment.
Advanced Decision Sciences Based on Deep Learning and Ensemble Learning Algorithms : A Practical Approach Using Python
Describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies.
Advance Concepts of Image Processing and Pattern Recognition : Effective Solution for Global Challenges
Explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc.
Adaptive Machine Learning Algorithms with Python : Solve Data Analytics and Machine Learing Problems on Edge Devices
Learn to use adaptive algorithms to solve real-world streaming data problems. This book covers a multitude of data processing challenges, ranging from the simple to the complex. At each step, you will gain insight into real-world use cases, find solutions, explore code used to solve these problems, and create new algorithms for your own use. You will: Apply adaptive algorithms to practical applications and examples / Understand the relevant data representation features and computational models for time-varying multi-dimensional data / Derive adaptive algorithms for mean, median, covariance, eigenvectors (PCA) and generalized eigenvectors with experiments on real data / Speed up your algorithms and put them to use on real-world stationary and non-stationary data / Master the applications of adaptive algorithms on critical edge device computation applications
A General introduction to data analytics
A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming. A guide to the reasoning behind data mining techniques. A unique illustrative example that extends throughout all the chapters. Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts
