[PDF] Capitalizing On Big Data eBook

Author : Mathangi Sri Ramachandran
Publisher : BPB Publications
Page : 295 pages
File Size : 32,52 MB
Release : 2022-12-03
Category : Computers
ISBN : 9355511582

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Unlock the Potential of Data Science and Machine Learning to Your Business and Organization KEY FEATURES ● Includes today's most popular applications powered by data science and machine learning technology. ● A solid primer on the entire data science lifecycle, detailed with examples. ● An integrated approach to demonstrating the use of Image Processing, Natural Language Processing, and Neural Networks in business. DESCRIPTION Can you foresee how your company and its products will benefit from data science? How can the results of using AI and ML in business be tracked and questioned? Do questions like ‘how do you build a data science team?’ keep popping into your head? All these strategic concerns and challenges are addressed in this book. Firstly, the book explores the evolution of decision-making based on empirical evidence. The book then helps compare the data-supported era with the current data-led era. It also discusses how to successfully run a data science project, the lifecycle of a data science project, and what it looks like. The book dives fairly in-depth into various today's data-led applications, highlights example datasets, discusses obstacles, and explains machine learning models and algorithms intuitively. This book covers structural and organizational considerations for making a data science team. The book helps recommend the use of optimal data science organization structure based on the company's level of development. Finally, the book explains data science's effects on businesses by assisting technological leaders. WHAT YOU WILL LEARN ● Learn the entire data science lifecycle and become fluent in each phase. ● Discover the world of supervised and unsupervised learning applications and structured and unstructured datasets. ● Discuss NLP's function, its potential, and the application of well-known methods like BERT and GPT3. ● Explain practical applications like automatic captioning, machine translation, and emotion recognition. ● Provide a framework for evaluating your team's data science skills and resources. WHO THIS BOOK IS FOR Startups, investors, small businesses, product management teams, CxO and all developing businesses desiring to leverage a data science team to gain the most from this book. The book also discusses the potential of practical applications of machine learning and AI for the future of businesses in banking and e-commerce. TABLE OF CONTENTS 1. Data-Driven Decisions from Beginning to Now 2. Data Science Life Cycle —Part 1 3. Data Science Life Cycle —Part 2 4. Deep Dive into AI 5. Applying AI with Structured Data—Banking 6. Applying AI with Structured Data 7. Applying AI with Structured Data—On-Demand Deliveries 8. AI in Natural Language Processing 9. Bringing It All Together

Author :
Publisher :
Page : pages
File Size : 22,89 MB
Release : 2015
Category :
ISBN :

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The race is on for big data adoption, with many organizations leading the way while others struggle to understand what it means and determine whether it is right for their organization or function. Break through the big data hype to understand the business implications of this evolving discipline.

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 2523 pages
File Size : 27,69 MB
Release : 2016-04-20
Category : Computers
ISBN : 1466698411

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The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Author : Abdelkader Hameurlain
Publisher : Springer Nature
Page : 139 pages
File Size : 35,53 MB
Release : 2020-08-12
Category : Computers
ISBN : 3662621991

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The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 43rd issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five revised selected regular papers. Topics covered include classification tasks, machine learning algorithms, top-k queries, business process redesign and a knowledge capitalization framework.

Author : Frederik Stjernfelt
Publisher : Springer Nature
Page : 295 pages
File Size : 19,9 MB
Release : 2019-01-01
Category : Freedom of speech
ISBN : 3030259684

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This open access monograph argues established democratic norms for freedom of expression should be implemented on the internet. Moderating policies of tech companies as Facebook, Twitter and Google have resulted in posts being removed on an industrial scale. While this moderation is often encouraged by governments - on the pretext that terrorism, bullying, pornography, "hate speech" and "fake news" will slowly disappear from the internet - it enables tech companies to censure our society. It is the social media companies who define what is blacklisted in their community standards. And given the dominance of social media in our information society, we run the risk of outsourcing the definition of our principles for discussion in the public domain to private companies. Instead of leaving it to social media companies only to take action, the authors argue democratic institutions should take an active role in moderating criminal content on the internet. To make this possible, tech companies should be analyzed whether they are approaching a monopoly. Antitrust legislation should be applied to bring those monopolies within democratic governmental oversight. Despite being in different stages in their lives, Anne Mette is in the startup phase of her research career, while Frederik is one of the most prolific philosophers in Denmark, the authors found each other in their concern about Free Speech on the internet. The book was originally published in Danish as Dit opslag er blevet fjernet - techgiganter & ytringsfrihed. Praise for 'Your Post has been Removed' "From my perspective both as a politician and as private book collector, this is the most important non-fiction book of the 21st Century. It should be disseminated to all European citizens. The learnings of this book and the use we make of them today are crucial for every man, woman and child on earth. Now and in the future." Jens Rohde, member of the European Parliament for the Alliance of Liberals and Democrats for Europe "This timely book compellingly presents an impressive array of information and analysis about the urgent threats the tech giants pose to the robust freedom of speech and access to information that are essential for individual liberty and democratic self-government. It constructively explores potential strategies for restoring individual control over information flows to and about us. Policymakers worldwide should take heed!" Nadine Strossen, Professor, New York Law School. Author, HATE: Why We Should Resist It with Free Speech, Not Censorship.

Author : Michael N. Jones
Publisher : Psychology Press
Page : 384 pages
File Size : 10,62 MB
Release : 2016-11-03
Category : Computers
ISBN : 1315413566

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The primary goal of this volume is to present cutting-edge examples of mining large and naturalistic datasets to discover important principles of cognition and to evaluate theories in a way that would not be possible without such scale. It explores techniques that have been underexploited by cognitive psychologists and explains how big data from numerous sources can inform researchers with different research interests and shed further light on how brain, cognition and behavior are interconnected. The book fills a major gap in the literature and has the potential to rapidly advance knowledge throughout the field. It is essential reading for any cognitive psychology researcher.

Author : VK Jain
Publisher : KHANNA PUBLISHING
Page : 655 pages
File Size : 42,35 MB
Release : 2017-01-01
Category : Education
ISBN : 938260913X

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This book introduces you to the Big Data processing techniques addressing but not limited to various BI (business intelligence) requirements, such as reporting, batch analytics, online analytical processing (OLAP), data mining and Warehousing, and predictive analytics. The book has been written on IBMs Platform of Hadoop framework. IBM Infosphere BigInsight has the highest amount of tutorial matter available free of cost on Internet which makes it easy to acquire proficiency in this technique. This therefore becomes highly vunerable coaching materials in easy to learn steps. The book optimally provides the courseware as per MCA and M. Tech Level Syllabi of most of the Universities. All components of big Data Platform like Jaql, Hive Pig, Sqoop, Flume , Hadoop Streaming, Oozie: HBase, HDFS, FlumeNG, Whirr, Cloudera, Fuse , Zookeeper and Mahout: Machine learning for Hadoop has been discussed in sufficient Detail with hands on Exercises on each.

Author : Carlos Cordon
Publisher : Springer
Page : 151 pages
File Size : 37,35 MB
Release : 2016-06-01
Category : Business & Economics
ISBN : 3319311328

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This book presents strategies and practices to allow everyday companies to cope with the fundamentally changing landscape of business models and to take advantage of the huge business opportunities arising from the advent of big data. It develops several case studies from companies in traditional industries like LEGO, Yamato and Mediq, but also examines small start-ups like Space Tango, which is partnering with major multinationals to develop new business models using big data. The book argues that businesses need to adapt and embark on their big data journey, helps them take the first step, and guides them along their way. It presents successful examples and deducts essential takeaway lessons from them, equipping executives to capitalize on big data and enabling them to make intelligent decisions in the big data transformation, giving their companies an essential competitive edge.

Author : Shriram Girishkumar Gajjar
Publisher :
Page : pages
File Size : 29,52 MB
Release : 2017
Category :
ISBN : 9780355763805

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Background: With the advances in communication technologies and the emergence of smart factories, large volumes of data are routinely collected and stored at high sampling rates. The data generation and collection are so fast-paced that humans have to rely on computers for consuming as well as processing the data. This necessitates development of algorithms and methods that can be used to improve process performance and facilitate process monitoring. My research interests are in application of multi-dimensional visualizations, advanced statistical and mathematical algorithms tailored to extract meaningful information from large data-sets collected in industrial plant operations and scientific experiments. These algorithms will at first, be able to unlock significant information from the large datasets. Second, they will provide accurate means to reduce process variability and boost performance. Third, they will allow discovery of the underlying process dynamics that can substantially improve decision-making. Finally, they will provide recommendations for steps that can be taken proactively to avoid sub-optimal and abnormal operations. Methods: 1. Visualization: A control chart is one of the primary techniques for statistical process monitoring of real-time data. However, monitoring hundreds of variables simultaneously using univariate control charts is difficult. An approach based on parallel coordinates is developed to address this challenge. 2. Data dimension reduction: Principal component analysis (PCA), a widely used multivariate technique with various applications ranging from facial recognition to clustering is implemented. One of the drawbacks of using PCA for dimension reduction is that most variable loadings are typically non-zero. Such non-zero variable loadings (NZL) make it difficult to interpret the derived principal components and may confound subsequent analyses. To address this challenge, Sparse Principal Component Analysis (SPCA) is used but specifying number of NZL for each sparse principal component is a numerically hard combinatorial problem. Evolutionary algorithms in conjunction with SPCA are implemented to tackle such combinatorial optimization problems and gain insights about the underlying dynamics of the data. Least Squares SPCA (LS SPCA) is then introduced wherein uncorrelatedness constraints on the components are imposed to obtain uncorrelated sparse loadings 3. Real-time analytics: A novel real-time fault detection, machine learning based diagnosis is developed. Summary: This dissertation, at first, will focus on determination of number of non-zero loadings in SPCA. Second, it will compare the performance of SPCA with PCA for process monitoring that also enables process knowledge discovery. Lastly, parallel coordinates and LS SPCA are introduced for process monitoring and validity of the proposed techniques will be demonstrated through a benchmark process simulator. Keywords: Fault detection, Fault diagnosis, Random Forests, Singular value decomposition, Principal component analysis (PCA), Sparse principal component analysis (SPCA), Least Squares Sparse principal component analysis (LS SPCA), Multivariate statistical process monitoring, Multidimensional visualization, Genetic Algorithms, Random Forests, Big Data, Historical data analysis, Tennessee Eastman process.