Автор: Halawi Leila, Clarke Amal, George Kelly Название: Harnessing the Power of Analytics ISBN: 3030897117 ISBN-13(EAN): 9783030897116 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This text highlights the difference between analytics and data science, using predictive analytic techniques to analyze different historical data, including aviation data and concrete data, interpreting the predictive models, and highlighting the steps to deploy the models and the steps ahead.
Название: Data-Driven Farming ISBN: 1032618922 ISBN-13(EAN): 9781032618920 Издательство: Taylor&Francis Рейтинг: Цена: 168430.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Название: Data-Driven Farming ISBN: 1032778725 ISBN-13(EAN): 9781032778723 Издательство: Taylor&Francis Рейтинг: Цена: 53070.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Sujatha R., Aarthy S. L., Vettriselvan R. Название: Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics ISBN: 0367466635 ISBN-13(EAN): 9780367466633 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems.
Apply cutting-edge AI techniques to your Dynamics 365 environment to create new solutions to old business problems
In Machine Learning with Dynamics 365 and Power Platform: The Ultimate Guide to Apply Predictive Analytics, an accomplished team of digital and data analytics experts delivers a practical and comprehensive discussion of how to integrate AI Builder with Dataverse and Dynamics 365 to create real-world business solutions. It also walks you through how to build powerful machine learning models using Azure Data Lake, Databricks, Azure Synapse Analytics.
The book is filled with clear explanations, visualizations, and working examples that get you up and running in your development of supervised, unsupervised, and reinforcement learning techniques using Microsoft machine learning tools and technologies. These strategies will transform your business verticals, reducing costs and manual processes in finance and operations, retail, telecommunications, and manufacturing industries.
The authors demonstrate:
What machine learning is all about and how it can be applied to your organization's Dynamics 365 and Power Platform Projects
The creation and management of environments for development, testing, and production of a machine learning project
How adopting machine learning techniques will redefine the future of your ERP/CRM system
Perfect for Technical Consultants, software developers, and solution architects, Machine Learning with Dynamics 365 and Power Platform is also an indispensable guide for Chief Technology Officers seeking an intuitive resource for how to implement machine learning in modern business applications to solve real-world problems.
Автор: Aspin Название: Pro DAX and Data Modeling in Power BI ISBN: 1484289943 ISBN-13(EAN): 9781484289945 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Develop powerful data models that bind data from disparate sources into a coherent whole. Then extend your data models using DAX–the query language that underpins Power BI–to create reusable measures to deliver finely-crafted custom calculations in your dashboards. This book starts off teaching you how to define and enhance the core structures of your data model to make it a true semantic layer that transforms complex data into familiar business terms. You’ll learn how to create calculated columns to solve basic analytical challenges. Then you’ll move up to mastering DAX measures to finely slice and dice your data. The book also shows how to handle temporal analysis in Power BI using a Date dimension. You will see how DAX Time Intelligence functions can simplify your analysis of data over time. Finally, the book shows how to extend DAX to filter and calculate datasets and develop DAX table functions and variables to handle complex queries. What You Will Learn * Create clear and efficient data models that support in-depth analytics * Define core attributes such as data types and standardized formatting consistently throughout a data model * Define cross-filtering settings to enhance the data model * Make use of DAX to create calculated columns and custom tables * Extend your data model with custom calculations and reusable measures using DAX * Perform time-based analysis using a Date dimension and Time Intelligence functions Who This Book Is For Everyone from the CEO to the Business Intelligence developer and from BI and Data architects and analysts to power users and IT managers can use this book to outshine the competition and create the data framework that they need and interactive dashboards using Power BI
Автор: Malik Hasmat, Ahmad MD Waseem, Kothari D. P. Название: Intelligent Data Analytics for Power and Energy Systems ISBN: 9811660808 ISBN-13(EAN): 9789811660801 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.
Автор: Malik Название: Intelligent Data Analytics for Power and Energy Systems ISBN: 9811660832 ISBN-13(EAN): 9789811660832 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book brings together state-of-the-art advances in intelligent data analytics as driver of the future evolution of PaE systems. In the modern power and energy (PaE) domain, the increasing penetration of renewable energy sources (RES) and the consequent empowerment of consumers as a central and active solution to deal with the generation and development variability are driving the PaE system towards a historic paradigm shift. The small-scale, diversity, and especially the number of new players involved in the PaE system potentiate a significant growth of generated data. Moreover, advances in communication (between IoT devices and M2M: machine to machine, man to machine, etc.) and digitalization hugely increased the volume of data that results from PaE components, installations, and systems operation. This data is becoming more and more important for PaE systems operation, maintenance, planning, and scheduling with relevant impact on all involved entities, from producers, consumer,s and aggregators to market and system operators. However, although the PaE community is fully aware of the intrinsic value of those data, the methods to deal with it still necessitate substantial enhancements, development and research. Intelligent data analytics is thereby playing a fundamental role in this domain, by enabling stakeholders to expand their decision-making method and achieve the awareness on the PaE environment. The editors also included demonstrated codes for presented problems for better understanding for beginners.
Автор: Sanjay Madria; Takahiro Hara Название: Big Data Analytics and Knowledge Discovery ISBN: 3319227289 ISBN-13(EAN): 9783319227283 Издательство: Springer Рейтинг: Цена: 52170.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. data warehouses; applications of big data analysis;
Автор: Boris Deliba?i?; Jorge E. Hern?ndez; Jason Papatha Название: Decision Support Systems V – Big Data Analytics for Decision Making ISBN: 3319185322 ISBN-13(EAN): 9783319185323 Издательство: Springer Рейтинг: Цена: 37270.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 'Big Data' Decision Making Use Cases.- The Roles of Big Data in the Decision-Support Process: An Empirical Investigation.- Cloud Enabled Big Data Business Platform for Logistics Services: A Research and Development Agenda.- Making Sense of Governmental Activities Over Social Media: A Data-Driven Approach.- Data-Mining and Expert Models for Predicting Injury Risk in Ski Resorts.- The Effects of Performance Ratios in Predicting Corporate Bankruptcy: The Italian Case.- A Tangible Collaborative Decision Support System for Various Variants of the Vehicle Routing Problem.- Decision Support Model for Participatory Management of Water Resource.- Modeling Interactions Among Criteria in MCDM Methods: A Review.
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