The growing presence of biologically-inspired processing has caused significant changes in data retrieval. With the ubiquity of these technologies, more effective and streamlined data processing techniques are available. Bio-Inspired Computing for Information Retrieval Applications is a key resource on the latest advances and research regarding current techniques that have evolved from biologically-inspired processes and its application to a variety of problems. Highlighting multidisciplinary...
Harness the power of Microsoft Fabric to develop data analytics solutions for various use cases guided by step-by-step instructions Key Features Explore Microsoft Fabric and its features through real-world examples Build data analytics solutions for lakehouses, data warehouses, real-time analytics, and data science Monitor, manage, and administer your Fabric platform and analytics system to ensure flexibility, performance, security, and control Purchase of the print or Kindle book includes a f...
Handbook of Data Structures and Applications (Chapman & Hall/CRC Computer and Information Science)
Although there are many advanced and specialized texts and handbooks on algorithms, until now there was no book that focused exclusively on the wide variety of data structures that have been reported in the literature. The Handbook of Data Structures and Applications responds to the needs of students, professionals, and researchers who need a mainstream reference on data structures by providing a comprehensive survey of data structures of various types. Divided into seven parts, the text begins...
Environmental Modeling with GIS
This book, based on an international conference held in 1991, is aimed at those with Geographic Information Systems (GIS) experience who need to know more about environmental modelling, and at environmental modellers who want to know more about GIS, its advantages, and its problems. The first part of the book describes the state of the art in GIS, environmental modelling, spatial statistics, and spatial databases. The second part reviews the state of integration in each of the major "process" ar...
Hands-On Artificial Intelligence on Google Cloud Platform
by Anand Deshpande, Manish Kumar, and Vikram Chaudhari
Develop robust AI applications with TensorFlow, Cloud AutoML, TPUs, and other GCP services Key Features Focus on AI model development and deployment in GCP without worrying about infrastructure Manage feature processing, data storage, and trained models using Google Cloud Dataflow Access key frameworks such as TensorFlow and Cloud AutoML to run your deep learning models Book Description With a wide range of exciting tools and libraries such as Google BigQuery, Google Cloud Dataflow, and Google C...
Level up your career by learning best practices for managing the data quality and integrity of your financial data Key Features Accelerate data integrity management using artificial intelligence-powered solutions Learn how business intelligence tools, ledger databases, and database locks solve data integrity issues Find out how to detect fraudulent transactions affecting financial report integrity Book DescriptionData integrity management plays a critical role in the success and effectiveness...
Many organizations today analyze and share large, sensitive datasets about individuals. Whether these datasets cover healthcare details, financial records, or exam scores, it's become more difficult for organizations to protect an individual's information through deidentification, anonymization, and other traditional statistical disclosure limitation techniques. This practical book explains how differential privacy (DP) can help. Authors Ethan Cowan, Michael Shoemate, and Mayana Pereira a...
Elasticsearch Data Modeling and Schema Design
by Steve Hoberman and Rafid Reaz
Use active machine learning with Python to improve the accuracy of predictive models, streamline the data analysis process, and adapt to evolving data trends, fostering innovation and progress across diverse fields Key Features Learn how to implement a pipeline for optimal model creation from large datasets and at lower costs Gain profound insights within your data while achieving greater efficiency and speed Apply your knowledge to real-world use cases and solve complex ML problems Purchase o...
Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R About This Book • Predict and use a probabilistic graphical models (PGM) as an expert system • Comprehend how your computer can learn Bayesian modeling to solve real-world problems • Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R package Who This Book Is For This book is for anyone who has to deal with lots of data a...
This guide provides information on data governance, data architecture, data development, database operations, data security, reference & master data, data warehousing & business intelligence, document & content management, meta data management, data quality and professional development--
Over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps About This Book • Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types • Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning • Authored by Ivan Idris, expert in python programming and proud author of eight highly reviewed books Who This Book Is For This book teaches Python data a...
Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you'll focus on particular analyses you can build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce. Data scientists and analysts will learn how to perform a wide range...
Azure Machine Learning Engineering
by Sina Fakhraee, Balamurugan Balakreshnan, and Megan Masanz
Fully build and productionize end-to-end machine learning solutions using Azure Machine Learning ServiceKey FeaturesAutomate complete machine learning solutions using Microsoft AzureUnderstand how to productionize machine learning modelsGet to grips with monitoring, MLOps, deep learning, distributed training, and reinforcement learningBook DescriptionData scientists working on productionizing machine learning (ML) workloads face a breadth of challenges at every step owing to the countless factor...
180 Gel�ste F�lle In Der DAX-Sprache (Power Bi: Gelöste Fälle, #1)
by Ramón Javier Castro Amador
Apache Spark 2: Data Processing and Real-Time Analytics
by Romeo Kienzler, Md. Rezaul Karim, Sridhar Alla, Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, and Shuen Mei
Build efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing frameworkKey FeaturesMaster the art of real-time big data processing and machine learning Explore a wide range of use-cases to analyze large data Discover ways to optimize your work by using many features of Spark 2.x and ScalaBook DescriptionApache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data proc...
DNA Computing and Molecular Programming (Theoretical Computer Science and General Issues, #6518)
This book constitutes the thoroughly refereed post-conference proceedings of the 16th International Conference on DNA Computing and Molecular Programming, DNA16, held in Hong Kong, China, in June 2010. The 16 revised full papers presented were carefully selected during two rounds of reviewing and improvement from 59 submissions. The papers are well balanced between theoretical and experimental work and address all areas that relate to biomolecular computing, including demonstrations of biomolecu...
Data Structures and Algorithm Analysis in C++, International Edition
by Mark A. Weiss
Data Structures and Algorithm Analysis in C++ is an advanced algorithms book that bridges the gap between traditional CS2 and Algorithms Analysis courses.As the speed and power of computers increases, so does the need for effective programming and algorithm analysis. By approaching these skills in tandem, Mark Allen Weiss teaches readers to develop well-constructed, maximally efficient programs using the C++ programming language.This book explains topics from binary heaps to sorting to NP-comple...
Analyses of the Department of Defense Acquisition Workforce
by Susan M Gates, Elizabeth Roth, Sinduja Srinivasan, and Lindsay Daugherty
Computational Technologies (De Gruyter Textbook)
In this book we describe the basic elements of present computational technologies that use the algorithmic languages C/C++. The emphasis is on GNU compilers and libraries, FOSS for the solution of computational mathematics problems and visualization of the obtained data. At the beginning, a brief introduction to C is given with emphasis on its easy use in scientific and engineering computations. We describe the basic elements of the language, such as variables, data types, executable statemen...