Machine Learning for Auditors: Automating Fraud Investigations Through Artificial Intelligence, Sekar Maris
Автор: Wang Brydon, Timothy Wang, Chien Ming Название: Automating Cities: Design, Construction, Operation and Future Impact ISBN: 9811586691 ISBN-13(EAN): 9789811586699 Издательство: Springer Рейтинг: Цена: 12856.00 р. 16070.00-20% Наличие на складе: Есть (1 шт.) Описание: This book highlights the latest advancements in the use of automated systems in the design, construction, operation and future of the built environment and its occupants.
Автор: Robert Layton Название: Algorithms for Automating Open Source Intelligence (OSINT) ISBN: 0128029161 ISBN-13(EAN): 9780128029169 Издательство: Elsevier Science Рейтинг: Цена: 5051.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: . Algorithms for Automating Open Source Intelligence (OSINT) presents information on the gathering of information and extraction of actionable intelligence from openly available sources, including news broadcasts, public repositories, and more recently, social media. As OSINT has applications in crime fighting, state-based intelligence, and social research, this book provides recent advances in text mining, web crawling, and other algorithms that have led to advances in methods that can largely automate this process. The book is beneficial to both practitioners and academic researchers, with discussions of the latest advances in applications, a coherent set of methods and processes for automating OSINT, and interdisciplinary perspectives on the key problems identified within each discipline. Drawing upon years of practical experience and using numerous examples, editors Robert Layton, Paul Watters, and a distinguished list of contributors discuss Evidence Accumulation Strategies for OSINT, Named Entity Resolution in Social Media, Analyzing Social Media Campaigns for Group Size Estimation, Surveys and qualitative techniques in OSINT, and Geospatial reasoning of open data.
Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems.
Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. The book also explores new approaches for integrating data privacy into machine learning pipelines.
Understand the machine learning management lifecycle
Implement data pipelines with Apache Airflow and Kubeflow Pipelines
Work with data using TensorFlow tools like ML Metadata, TensorFlow Data Validation, and TensorFlow Transform
Analyze models with TensorFlow Model Analysis and ship them with the TFX Model Pusher Component after the ModelValidator TFX Component confirmed that the analysis results are an improvement
Deploy models in a variety of environments with TensorFlow Serving, TensorFlow Lite, and TensorFlow.js
Learn methods for adding privacy, including differential privacy with TensorFlow Privacy and federated learning with TensorFlow Federated
Design model feedback loops to increase your data sets and learn when to update your machine learning models
Автор: Tomlinson Joe, Maxwell Jack Название: Experiments in Automating Immigration Systems ISBN: 1529219841 ISBN-13(EAN): 9781529219845 Издательство: Marston Book Services Рейтинг: Цена: 8512.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Identifying a pattern of risky experimentation with automated systems in the Home Office, this book outlines precautionary measures that are essential to ensure that society benefits from government automation without exposing individuals to unacceptable risks.
Автор: Sandra Marcus Название: Automating Knowledge Acquisition for Expert Systems ISBN: 1468471244 ISBN-13(EAN): 9781468471243 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In June of 1983, our expert systems research group at Carnegie Mellon University began to work actively on automating knowledge acquisition for expert systems.
Автор: Yun-Heh Chen-Burger; Dave Robertson Название: Automating Business Modelling ISBN: 1849969345 ISBN-13(EAN): 9781849969345 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Enhances the use of enterprise models as an effective communication medium between business and technical personnel. Details the blue-print of the to-be developed business system.
Описание: This book highlights the latest advancements in the use of automated systems in the design, construction, operation and future of the built environment and its occupants.
Автор: F.D. Kamareddine Название: Thirty Five Years of Automating Mathematics ISBN: 9048164400 ISBN-13(EAN): 9789048164400 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: THIRTY FIVE YEARS OF AUTOMATING MATHEMATICS: DEDICATED TO 35 YEARS OF DE BRUIJN`S AUTOMATH N. De Bruijn`s contributions to mathematics also included his work on generalized function theory, analytic number theory, optimal control, quasicrystals, the mathematical analysis of games and much more.
Описание: This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user’s perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification.
Автор: Gisele L. Pappa; Alex Freitas Название: Automating the Design of Data Mining Algorithms ISBN: 3642261256 ISBN-13(EAN): 9783642261251 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This unique text seeks to automate the design of a data mining algorithm. It first overviews data mining and evolutionary algorithms then discusses the design of a new genetic programming system for automating the design of full rule induction algorithms.
Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 11504.00 р. Наличие на складе: Поставка под заказ.
Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
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