L Analisi Dei Big Data Con Python Le Migliori Tecniche Per Aggregare I Dati

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Handbook of Research for Big Data

Author: Brojo Kishore Mishra
language: en
Publisher: Apple Academic Press
Release Date: 2022
"Data has become a valuable asset like never before. Today the challenge is not a shortage of data but the need for techniques and methods capable enough to be able to glean valuable insights from the fast-flowing mass of Big Data. This new volume, Handbook of Research for Big Data: Concepts and Techniques, helps to meet the challenge of managing and using Big Data by presenting new research on various technological advances in the field. The chapters in the book present information on important applications, concepts, and technologies for Big Data in the present industry and market scenario. It looks at research domain issues and their solutions as well as various research case studies, research plans, methodologies, and related data sets for the four Vs: volume, velocity, variety, and veracity. Chapters discuss Big Data in governance, transportation, disaster management, epidemiology, and more. The book covers design and analysis of reconfigurable computing of SoC for IoT, data mining techniques and applications, the use of natural language processing in big data, and more. The volume is a valuable resource for researchers from both academia and industry to learn about and enhance their knowledge and skills in the broad area of big data computing and applications"--
Formal Languages and Compilation

Author: Stefano Crespi Reghizzi
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-10-16
This revised and expanded new edition elucidates the elegance and simplicity of the fundamental theory underlying formal languages and compilation. Retaining the reader-friendly style of the 1st edition, this versatile textbook describes the essential principles and methods used for defining the syntax of artificial languages, and for designing efficient parsing algorithms and syntax-directed translators with semantic attributes. Features: presents a novel conceptual approach to parsing algorithms that applies to extended BNF grammars, together with a parallel parsing algorithm (NEW); supplies supplementary teaching tools at an associated website; systematically discusses ambiguous forms, allowing readers to avoid pitfalls; describes all algorithms in pseudocode; makes extensive usage of theoretical models of automata, transducers and formal grammars; includes concise coverage of algorithms for processing regular expressions and finite automata; introduces static program analysis based on flow equations.