Small Summaries For Big Data
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Small Summaries For Big Data
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Author : Graham Cormode
language : en
Publisher: Cambridge University Press
Release Date : 2020-11-12
Small Summaries For Big Data written by Graham Cormode and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.
A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.
Web And Big Data
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Author : Wenjie Zhang
language : en
Publisher: Springer Nature
Release Date : 2024-08-27
Web And Big Data written by Wenjie Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-27 with Computers categories.
The five-volume set LNCS 14961, 14962, 14963, 14964 and 14965 constitutes the refereed proceedings of the 8th International Joint Conference on Web and Big Data, APWeb-WAIM 2024, held in Jinhua, China, during August 30–September 1, 2024. The 171 full papers presented in these proceedings were carefully reviewed and selected from 558 submissions. The papers are organized in the following topical sections: Part I: Natural language processing, Generative AI and LLM, Computer Vision and Recommender System. Part II: Recommender System, Knowledge Graph and Spatial and Temporal Data. Part III: Spatial and Temporal Data, Graph Neural Network, Graph Mining and Database System and Query Optimization. Part IV: Database System and Query Optimization, Federated and Privacy-Preserving Learning, Network, Blockchain and Edge computing, Anomaly Detection and Security Part V: Anomaly Detection and Security, Information Retrieval, Machine Learning, Demonstration Paper and Industry Paper.
Technologies And Applications For Big Data Value
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Author : Edward Curry
language : en
Publisher: Springer Nature
Release Date : 2022-04-28
Technologies And Applications For Big Data Value written by Edward Curry and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-28 with Computers categories.
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part “Technologies and Methods” contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part “Processes and Applications” details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.
Small Data
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Author : Martin Lindstrom Company
language : en
Publisher: Hachette UK
Release Date : 2016-03-10
Small Data written by Martin Lindstrom Company and has been published by Hachette UK this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-10 with Business & Economics categories.
The New York Times Bestseller named one of the "Most Important Books of 2016" by Inc, and a Forbes 2016 "Must Read Business Book" 'If you love 'Bones' and 'CSI', this book is your kind of candy' Paco Underhill, author of Why We Buy 'Martin's best book to date. A personal, intuitive, powerful way to look at making an impact with your work' Seth Godin, author of Purple Cow Martin Lindstrom, one of Time Magazine's 100 Most Influential People in The World and a modern-day Sherlock Holmes, harnesses the power of "small data" in his quest to discover the next big thing. In an era where many believe Big Data has rendered human perception and observation 'old-school' or passé, Martin Lindstrom shows that mining and matching technological data with up-close psychological insight creates the ultimate snapshot of who we really are and what we really want. He works like a modern-day Sherlock Holmes, accumulating small clues - the progressively weaker handshakes of Millenials, a notable global decrease in the use of facial powder, a change in how younger consumers approach eating ice cream cones - to help solve a stunningly diverse array of challenges. In Switzerland, a stuffed teddy bear in a teenage girl's bedroom helped revolutionise 1,000 stores - spread across twenty countries - for one of Europe's largest fashion retailers. In Dubai, a distinctive bracelet strung with pearls helped Jenny Craig offset its declining membership in the United States and increase loyalty by 159% in only one year. In China, the look of a car dashboard led to the design of the iRobot, or Roomba, floor cleaner - a great success story. SMALL DATA combines armchair travel with forensic psychology in an interlocking series of international clue-gathering detective stories. It shows Lindstrom using his proprietary CLUES Framework - where big data is merely one part of the overall puzzle - to get radically close to consumers and come up with the counter-intuitive insights that have in some cases helped transform entire industries. SMALL DATA presents a rare behind-the-scenes look at what it takes to create global brands, and reveals surprising and counter-intuitive truths about what connects us all as humans.
Sharing Data And Models In Software Engineering
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Author : Tim Menzies
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-12-22
Sharing Data And Models In Software Engineering written by Tim Menzies and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-22 with Computers categories.
Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects. - Shares the specific experience of leading researchers and techniques developed to handle data problems in the realm of software engineering - Explains how to start a project of data science for software engineering as well as how to identify and avoid likely pitfalls - Provides a wide range of useful qualitative and quantitative principles ranging from very simple to cutting edge research - Addresses current challenges with software engineering data such as lack of local data, access issues due to data privacy, increasing data quality via cleaning of spurious chunks in data
Summary Big Data
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Author : BusinessNews Publishing,
language : en
Publisher: Primento
Release Date : 2014-11-12
Summary Big Data written by BusinessNews Publishing, and has been published by Primento this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-12 with Business & Economics categories.
The must-read summary of Viktor Mayer-Schonberg and Kenneth Cukier's book: "Big Data: A Revolution that Will Transform How We Live, Work and Think". This complete summary of the ideas from Viktor Mayer-Schonberg and Kenneth Cukier's book "Big Data" explains that the concept of "big data" means using huge quantities of data to make better predictions based on patterns, rather than trying to understand the underlying causes in more detail. In their book, the authors highlight the many ways in which big data will be a source of new economic value and innovation in the future. This summary also demonstrates that this change in the way information is analysed will transform the way everyone lives and interacts in the world. Added-value of this summary: • Save time • Understand key concepts • Expand your knowledge To learn more, read "Big Data" and discover how the way we use data is evolving and what this means for the future.
The Nature Of Computation Logic Algorithms Applications
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Author : Paola Bonizzoni
language : en
Publisher: Springer
Release Date : 2013-06-03
The Nature Of Computation Logic Algorithms Applications written by Paola Bonizzoni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-03 with Computers categories.
This book constitutes the refereed proceedings of the 9th Conference on Computability in Europe, CiE 2013, held in Milan, Italy, in July 2013. The 48 revised papers presented together with 1 invited lecture and 2 tutorials were carefully reviewed and selected with an acceptance rate of under 31,7%. Both the conference series and the association promote the development of computability-related science, ranging over mathematics, computer science and applications in various natural and engineering sciences such as physics and biology, and also including the promotion of related non-scientific fields such as philosophy and history of computing.
Data Analysis With Python And Pyspark
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Author : Jonathan Rioux
language : en
Publisher: Simon and Schuster
Release Date : 2022-04-12
Data Analysis With Python And Pyspark written by Jonathan Rioux and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-12 with Computers categories.
Think big about your data! PySpark brings the powerful Spark big data processing engine to the Python ecosystem, letting you seamlessly scale up your data tasks and create lightning-fast pipelines. In Data Analysis with Python and PySpark you will learn how to: Manage your data as it scales across multiple machines Scale up your data programs with full confidence Read and write data to and from a variety of sources and formats Deal with messy data with PySpark’s data manipulation functionality Discover new data sets and perform exploratory data analysis Build automated data pipelines that transform, summarize, and get insights from data Troubleshoot common PySpark errors Creating reliable long-running jobs Data Analysis with Python and PySpark is your guide to delivering successful Python-driven data projects. Packed with relevant examples and essential techniques, this practical book teaches you to build pipelines for reporting, machine learning, and other data-centric tasks. Quick exercises in every chapter help you practice what you’ve learned, and rapidly start implementing PySpark into your data systems. No previous knowledge of Spark is required. About the technology The Spark data processing engine is an amazing analytics factory: raw data comes in, insight comes out. PySpark wraps Spark’s core engine with a Python-based API. It helps simplify Spark’s steep learning curve and makes this powerful tool available to anyone working in the Python data ecosystem. About the book Data Analysis with Python and PySpark helps you solve the daily challenges of data science with PySpark. You’ll learn how to scale your processing capabilities across multiple machines while ingesting data from any source—whether that’s Hadoop clusters, cloud data storage, or local data files. Once you’ve covered the fundamentals, you’ll explore the full versatility of PySpark by building machine learning pipelines, and blending Python, pandas, and PySpark code. What's inside Organizing your PySpark code Managing your data, no matter the size Scale up your data programs with full confidence Troubleshooting common data pipeline problems Creating reliable long-running jobs About the reader Written for data scientists and data engineers comfortable with Python. About the author As a ML director for a data-driven software company, Jonathan Rioux uses PySpark daily. He teaches the software to data scientists, engineers, and data-savvy business analysts. Table of Contents 1 Introduction PART 1 GET ACQUAINTED: FIRST STEPS IN PYSPARK 2 Your first data program in PySpark 3 Submitting and scaling your first PySpark program 4 Analyzing tabular data with pyspark.sql 5 Data frame gymnastics: Joining and grouping PART 2 GET PROFICIENT: TRANSLATE YOUR IDEAS INTO CODE 6 Multidimensional data frames: Using PySpark with JSON data 7 Bilingual PySpark: Blending Python and SQL code 8 Extending PySpark with Python: RDD and UDFs 9 Big data is just a lot of small data: Using pandas UDFs 10 Your data under a different lens: Window functions 11 Faster PySpark: Understanding Spark’s query planning PART 3 GET CONFIDENT: USING MACHINE LEARNING WITH PYSPARK 12 Setting the stage: Preparing features for machine learning 13 Robust machine learning with ML Pipelines 14 Building custom ML transformers and estimators
The Ethics Of Personal Data Collection In International Relations
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Author : Colette Mazzucelli
language : en
Publisher: Anthem Press
Release Date : 2022-04-05
The Ethics Of Personal Data Collection In International Relations written by Colette Mazzucelli and has been published by Anthem Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-05 with Philosophy categories.
This volume’s relevance may be explained, first and foremost, during a time of unprecedented loss of life around the world each day. The data, which is oftentimes incomplete and misleading, nonetheless reveals the state as deficient as well as negligent in its response to social healthcare needs. This volume attests to the fact that pressing global public health concerns are ever present as subjects of societal discourse and debate in developed and developing states. Moreover, the COVID-19 pandemic makes the omission of the ethics of personal data collection analysis in the international relations literature even more salient given the rise of contact tracing and increased uses of mobile phone Apps to track citizens by states and firms across the globe, as this volume’s chapters analyzing the responses to COVID-19 in Iran and Taiwan explain.
Probabilistic Machine Learning
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Author : Kevin P. Murphy
language : en
Publisher: MIT Press
Release Date : 2023-08-15
Probabilistic Machine Learning written by Kevin P. Murphy and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-15 with Computers categories.
An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty. An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference. With contributions from top scientists and domain experts from places such as Google, DeepMind, Amazon, Purdue University, NYU, and the University of Washington, this rigorous book is essential to understanding the vital issues in machine learning. Covers generation of high dimensional outputs, such as images, text, and graphs Discusses methods for discovering insights about data, based on latent variable models Considers training and testing under different distributions Explores how to use probabilistic models and inference for causal inference and decision making Features online Python code accompaniment