“…This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more. …”

“…The realization that the genetic repertoire of a biological species always encompasses more than the genome of each individual is one of the earliest examples of big data in biology that opened biology to the unbounded. …”

Tabla de Contenidos: “…Internet of Things -- Consistent User Experience Across Devices -- Cloud Computing -- Big Data Analytics -- Artificial Intelligence -- Business Benefits and Risks -- New Security Capabilities -- Baseline Security -- Protected Environments -- Encryption -- Hardware Acceleration -- Enhanced Recovery -- AI-Based Security and Automation -- Context-Aware Security -- Cloud Security and Context Awareness -- Security Analytics and Data Protection -- Conclusion -- Chapter 9: Corporate Social Responsibility: The Ethics of Managing Information Risk -- The Expanding Scope of Corporate Social Responsibility -- The Evolution of Technology and Its Impact -- Maintaining Society's Trust -- The Ethics of Managing Information Risk -- Conclusion -- Chapter 10: The 21st Century CISO -- Chief Trust Officer -- The Z-Shaped Individual -- Foundational Skills -- Becoming a Storyteller -- Fear Is Junk Food -- Accentuating the Positive -- Demonstrating the Reality of Risk -- The CISO's Sixth Sense -- Taking Action at the Speed of Trust -- The CISO as a Leader -- Learning from Other Business Leaders -- Voicing Our Values -- Discussing Information Risk at Board Level -- Conclusion -- Chapter 11: Performance Coaching -- How to Use the Tables -- Independence and Initiative -- Efficiency and Effectiveness -- Commitment -- Professionalism -- Discipline -- Teamwork -- Problem-Solving -- Communication -- Listening -- Style -- Clarity -- Goal-Setting -- Conclusion -- Appendix A -- Index…”

Tabla de Contenidos: “…Components of IoT -- 1.2. Big Data Revolution -- 1.2.1. Big data and IoT -- 1.3. …”

Tabla de Contenidos: “…Chapter 6: Advanced Search Examples -- Using subsearches to find loosely related events -- Subsearch -- Subsearch caveats -- Nested subsearches -- Using transaction -- Using transaction to determine session length -- Calculating the aggregate of transaction statistics -- Combining subsearches with transaction -- Determining concurrency -- Using transaction with concurrency -- Using concurrency to estimate server load -- Calculating concurrency with a by clause -- Calculating events per slice of time -- Using timechart -- Calculating average requests per minute -- Calculating average events per minute, per hour -- Rebuilding top -- Acceleration -- Big data - summary strategy -- Report acceleration -- Report acceleration availability -- Version 7.0 advancements in metrics -- Definition of a Splunk metric -- Using Splunk metrics -- Creating a metrics index -- Creating a UDP or TCP data input -- Summary -- Chapter 7: Extending Search -- Using tags to simplify search -- Using event types to categorize results -- Using lookups to enrich data -- Defining a lookup table file -- Defining a lookup definition -- Defining an automatic lookup -- Troubleshooting lookups -- Using macros to reuse logic -- Creating a simple macro -- Creating a macro with arguments -- Creating workflow actions -- Running a new search using values from an event -- Linking to an external site -- Building a workflow action to show field context -- Building the context workflow action -- Building the context macro -- Using external commands -- Extracting values from XML -- xmlkv -- XPath -- Using Google to generate results -- Summary -- Chapter 8: Working with Apps -- Defining an app -- Included apps -- Installing apps -- Installing apps from Splunkbase -- Using Geo Location Lookup Script -- Using Google Maps -- Installing apps from a file -- Building your first app -- Editing navigation…”

Tabla de Contenidos: “…Cover -- Copyright -- Credits -- Foreword -- About the Authors -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: The Big Data Science Ecosystem -- Introducing the Big Data ecosystem -- Data management -- Data management responsibilities -- The right tool for the job -- Overall architecture -- Data Ingestion -- Data Lake -- Reliable storage -- Scalable data processing capability -- Data science platform -- Data Access -- Data technologies -- The role of Apache Spark -- Companion tools -- Apache HDFS -- Advantages -- Disadvantages -- Installation -- Amazon S3 -- Advantages -- Disadvantages -- Installation -- Apache Kafka -- Advantages -- Disadvantages -- Installation -- Apache Parquet -- Advantages -- Disadvantages -- Installation -- Apache Avro -- Advantages -- Disadvantages -- Installation -- Apache NiFi -- Advantages -- Disadvantages -- Installation -- Apache YARN -- Advantages -- Disadvantages -- Installation -- Apache Lucene -- Advantages -- Disadvantages -- Installation -- Kibana -- Advantages -- Disadvantages -- Installation -- Elasticsearch -- Advantages -- Disadvantages -- Installation -- Accumulo -- Advantages -- Disadvantages -- Installation -- Summary -- Chapter 2: Data Acquisition -- Data pipelines -- Universal ingestion framework -- Introducing the GDELT news stream -- Discovering GDELT in real-time -- Our first GDELT feed -- Improving with publish and subscribe -- Content registry -- Choices and more choices -- Going with the flow -- Metadata model -- Kibana dashboard -- Quality assurance -- [Example 1 - Basic quality checking, no contending users] -- Example 1 - Basic quality checking, no contending users -- Example 2 - Advanced quality checking, no contending users -- Example 3 - Basic quality checking, 50% utility due to contending users -- Summary…”

Tabla de Contenidos: “…Mehrere Rangfolgen erstellen -- Reporting-Funktionen -- Fenstergrenzen -- lag und lead -- Verketten von Spaltenwerten -- Testen Sie Ihr Wissen -- Übung 16-1 -- Übung 16-2 -- Übung 16-3 -- Kapitel 17: Mit großen Datenbanken arbeiten -- Partitionieren -- Partitionierungskonzepte -- Tabellen partitionieren -- Indizes partitionieren -- Partitionierungsmethoden -- Vorteile des Partitionierens -- Clustering -- Sharding -- Big Data -- Hadoop -- NoSQL und Dokumentendatenbanken -- Cloud Computing -- Zusammenfassung -- Kapitel 18: SQL und Big Data -- Einführung in Apache Drill -- Dateien mit Drill abfragen -- MySQL mit Drill abfragen -- MongoDB mit Drill abfragen -- Drill mit mehreren Datenquellen verwenden -- Die Zukunft von SQL -- Anhang A: ER-Diagramm der Musterdatenbank -- Anhang B: Lösungen zu den Übungen -- Index…”

Tabla de Contenidos: “…Chapter 10 Discovering Graph Secrets -- Envisioning Social Networks as Graphs -- Clustering networks in groups -- Discovering communities -- Navigating a Graph -- Counting the degrees of separation -- Walking a graph randomly -- Chapter 11 Getting the Right Web page -- Finding the World in a Search Engine -- Searching the Internet for data -- Considering how to find the right data -- Explaining the PageRank Algorithm -- Understanding the reasoning behind the PageRank algorithm -- Explaining the nuts and bolts of PageRank -- Implementing PageRank -- Implementing a Python script -- Struggling with a naive implementation -- Introducing boredom and teleporting -- Looking inside the life of a search engine -- Considering other uses of PageRank -- Going Beyond the PageRank Paradigm -- Introducing semantic queries -- Using AI for ranking search results -- Part 4 Wrangling Big Data -- Chapter 12 Managing Big Data -- Transforming Power into Data -- Understanding Moore's implications -- Finding data everywhere -- Getting algorithms into business -- Streaming Flows of Data -- Analyzing streams with the right recipe -- Reserving the right data -- Sketching an Answer from Stream Data -- Filtering stream elements by heart -- Demonstrating the Bloom filter -- Finding the number of distinct elements -- Learning to count objects in a stream -- Chapter 13 Parallelizing Operations -- Managing Immense Amounts of Data -- Understanding the parallel paradigm -- Distributing files and operations -- Employing the MapReduce solution -- Working Out Algorithms for MapReduce -- Setting up a MapReduce simulation -- Inquiring by mapping -- Chapter 14 Compressing and Concealing Data -- Making Data Smaller -- Understanding encoding -- Considering the effects of compression -- Choosing a particular kind of compression -- Choosing your encoding wisely…”

Tabla de Contenidos: “…Propositions/acts passed by other countries -- Special regulations for children and minority groups -- Promoting equality for minority groups -- Educational initiatives -- International AI initiatives and cooperative actions -- Next steps for trustworthy AI -- Proposed solutions and improvement areas -- Summary -- Further reading -- Part 2: Building Blocks and Patterns for a Next-Generation AI Ecosystem -- Chapter 4: Privacy Management in Big Data and Model Design Pipelines -- Technical requirements -- Designing privacy-proven pipelines -- Big data pipelines -- Architecting model design pipelines -- Incremental/continual ML training and retraining -- Scaling defense pipelines -- Enabling differential privacy in scalable architectures -- Designing secure microservices -- Vault -- Cloud security architecture -- Developing in a sandbox environment -- Managing secrets in cloud orchestration services -- Monitoring and threat detection -- Summary -- Further reading -- Chapter 5: ML Pipeline, Model Evaluation, and Handling Uncertainty -- Technical requirements -- Understanding different components of ML pipelines -- ML tasks and algorithms -- Uncertainty in ML -- Types of uncertainty -- Quantifying uncertainty -- Uncertainty in regression tasks -- Uncertainty in classification tasks -- Tools for benchmarking and quantifying uncertainty -- The Uncertainty Baselines library -- Keras-Uncertainty -- Robustness metrics -- Summary -- References -- Chapter 6: Hyperparameter Tuning, MLOps, and AutoML -- Technical requirements -- Introduction to AutoML -- Introducing H2O AutoML -- Understanding Amazon SageMaker Autopilot -- The need for MLOps -- TFX - a scalable end-to-end platform for AI/ML workflows -- Understanding Kubeflow -- Katib for hyperparameter tuning -- Vertex AI -- Datasets -- Training and experiments in Vertex AI -- Vertex AI Workbench -- Summary…”

Tabla de Contenidos: “…Cover -- Series Page -- Title Page -- Copyright Page -- Dedication Page -- Contents -- List of Figures -- List of Tables -- Foreword -- Preface -- Acknowledgments -- Acronyms -- Chapter 1 IoT-Based Health Monitoring Using a Hybrid Machine Learning Model -- 1.1 Introduction -- 1.2 Related Works -- 1.3 Research Gap -- 1.4 Proposed Model -- 1.4.1 Model Analysis with Result and Discussion -- 1.4.2 Dataset Description -- 1.4.3 Model Description -- 1.5 Conclusion -- References -- 2 Addressing Overcrowding: A Plight for Smart Cities -- 2.1 Introduction -- 2.1.1 Smart Industry 4.0 -- 2.1.2 IoT and IIoT -- 2.1.3 IoT - A Basis of Big Data -- 2.1.4 Smart Cities -- 2.2 Overcrowding -- 2.2.1 Causes -- 2.2.2 Consequences -- 2.2.3 Challenges -- 2.3 Existing Applications -- 2.3.1 Traffic Congestion -- 2.3.2 Tourism Control -- 2.3.3 Sustainable Usage of Resources -- 2.3.4 Housing and Infrastructure -- 2.3.5 Public Safety and Security -- 2.4 Modified PSO for Optimal Path in Crowded Areas -- 2.4.1 Step 1: Modeling the Environment and Obstacles -- 2.4.2 Step 2: Particle Swarm Initialization -- 2.4.3 Step 3: Evaluating the Fitness Function -- 2.4.4 Step 4: Particle Position and Velocity Update -- 2.5 Scope -- 2.6 Conclusion -- References -- Chapter 3 Smart Sensors for Environmental Monitoring in Industry 4.0 -- 3.1 Introduction to Smart Sensors for Environmental Monitoring in Industry 4.0 -- 3.1.1 Basic Concepts of Industry 4.0 and Environmental Monitoring -- 3.1.2 Overview of Smart Sensors and Their Applications in Industry 4.0 -- 3.1.3 Challenges in Smart Sensor Design and Implementation for Environmental Monitoring in Industry 4.0 -- 3.2 State-of-the-Art of Smart Sensors for Environmental Monitoring in Industry 4.0 and Real-World Applications -- 3.2.1 Types of Smart Sensors for Environmental Monitoring in Industry 4.0.…”

Tabla de Contenidos: “…-- 1.8.1 Python Standard Library -- 1.8.2 Data-Science Libraries -- 1.9 Other Popular Programming Languages -- 1.10 Test-Drives: Using IPython and Jupyter Notebooks -- 1.10.1 Using IPython Interactive Mode as a Calculator -- 1.10.2 Executing a Python Program Using the IPython Interpreter -- 1.10.3 Writing and Executing Code in a Jupyter Notebook -- 1.11 Internet and World Wide Web -- 1.11.1 Internet: A Network of Networks -- 1.11.2 World Wide Web: Making the Internet User-Friendly -- 1.11.3 The Cloud -- 1.11.4 Internet of Things -- 1.12 Software Technologies -- 1.13 How Big Is Big Data? -- 1.13.1 Big Data Analytics -- 1.13.2 Data Science and Big Data Are Making a Difference: Use Cases -- 1.14 Case Study-A Big-Data Mobile Application -- 1.15 Intro to Data Science: Artificial Intelligence-at the Intersection of CS and Data Science -- 2. …”

Tabla de Contenidos: “…-- 2.3.5 Challenges With the Database in the Healthcare System -- 2.4 Big Data and Database Security and Protection -- 2.4.1 What Is Big Data -- 2.4.2 Five V's of Big Data -- 2.4.2.1 Volume…”

Tabla de Contenidos: “…. -- LO QUE DEMORÓ 200.000 AÑOS EN OCURRIR LO ESTAMOS VIVIENDO EN 50: EXPANSIÓN DE (...) -- BIG DATA EN ACCIÓN -- ¿CON QUÉ FRECUENCIA CUMPLIMOS NUESTRO PRESUPUESTO? …”
Acceso restringido con credenciales UPSA

Tabla de Contenidos: “…. -- LO QUE DEMORÓ 200.000 AÑOS EN OCURRIR LO ESTAMOS VIVIENDO EN 50: EXPANSIÓN DE (...) -- BIG DATA EN ACCIÓN -- ¿CON QUÉ FRECUENCIA CUMPLIMOS NUESTRO PRESUPUESTO? …”
Acceso restringido con credenciales UPSA

Tabla de Contenidos: “…Singapore’s Experience in Analyzing Labor Market Using Artificial Intelligence (AI) and Big Data Analytics -- 28. Funzi Uses the Power of Mobile to Give Everyone Cost-Effective Access to Quality Learning -- 29. …”

Tabla de Contenidos: “…1 -- Introduction: Genomics, Health and Society, Sahra Gibbon, Barbara Prainsack, Stephen Hilgartner and Janelle Lamoreaux -- --Section One: Genomic/DNA-based Technologies in the Clinic and Beyond -- --2 Introduction, Sabina Leonelli -- --3 Biomedicalisation in the Postgenomic Age, Catherine Bliss -- --4 Genomics and Big Data in Biomedicine, Sabina Leonelli and Niccolo Tempini -- --5 Mainstreaming Genomics and Personal Genetic Testing, Susan Kelly, Sally Wyatt and Anna Harris -- --6 Bringing Genetics into the Clinic: The Evolution of Genetic Testing and Counselling, Ilana Lowy -- --7 From Quality Control to Informed Choice: Understanding "Good Births" and Prenatal Genetic Testing in Contemporary Urban China, Jianfeng Zhu and Dong Dong -- --Section Two: Genomic Technologies in the Bioeconomy -- --8 Introduction, Claire Marris -- --9 Limits to Biocapital, Margaret Chiappetta and Kean Birch -- --10 Gendered Bioeconomies, Janelle Lamoreaux -- --11 Genomic Hope: Promise in the Bioeconomy, Paul Martin -- --12 Neoliberalism on Drugs: Genomics and the Political Economy of Medicine, Edward Nik-Khah -- --13 The Value of the Imagined Biological in Policy and Society: Somaticizing and Economising British Subject(ivitie)s, Martyn Pickersgill -- --14 Responsible Research and Innovation (RRI), Ulrike Felt -- --Section Three: Current Challenges in the Governance of Medical Genomics -- --15 Introduction, Stephen Hilgartner -- --16 The Human Genome Project and the Legacy of its Ethics Programs, Stephen Hilgartner -- --17 Patenting, Shobita Parthasarathy -- --18 Genomic Platforms and Clinical Research, Alberto Cambrosio, Etienne Vignola-Gagn, Nicole Nelson, Peter Keating, Pascale Bourret -- --19 Diagnostics, Stuart Hogarth -- --20 Collection and Protection of Personal Health Data, Edward Dove -- --21 In CRISPRs World: Genome Editing and the Politics of Global Science, Ben Hurlbut -- --Section Four: Diversity and Justice -- --22 Introduction, Sahra Gibbon and Barbara Prainsack -- --23 Disability and the Challenge of Genomics, Jackie Lee Scully -- --24 Eugenics and Enhancement in Contemporary Genomics, Silvia Camporesi and Giulia Cavaliere -- --25 Genomics and Insurance, Ine van Hoyweghen -- --26 Power Asymmetries, Participation, and the Idea of Personalised Medicine, Barbara Prainsack -- --27 Excavating Difference: Race in Genomic Medicine, Sandra Lee -- --28 Genomics in Emerging and Developing Economies, Duana Fullwileyand Sahra Gibbon -- --Section Five: Crossing Boundaries -- --29 Introduction, Janelle Lamoreaux -- --30 Epigenetics, Margaret Lock -- --31 Environmental Epigenetics and Suicide Risk at a Molecular Scale, Stephanie Lloyd and Eugene Raikhel -- --32 Stem Cells, Global Cells, Local Cultures, Jennifer Liu -- --33 Co-producing Animal Models and Genetic Science, Carrie Friese -- --34 Making Microbiomes, Amber Benezra -- --35 Behavior Genetics: Boundary Crossings and Epistemic Cultures, Nicole Nelson and Aaron Panofsky -- --36 Synthetic Biology, Jane Calvert, Dominic Berry and Deborah Scott…”

Tabla de Contenidos: “…; Chips, Chipsets, SoCs, and Modules; Some History and Gossip; Attributes of Bluetooth Smart Chipsets; Summary; So Many Vendors, So Little Time; A Platform Decision; Volume; Summary; Planning; Placement; Propagation; Procurement; Permission; Privacy/Public Notices; Process; People; Summary; Fleet Management Functions; Fleet Management Standards; Summary; Big Data…”

Tabla de Contenidos:

Tabla de Contenidos: “…The consumer marketplaceInsider insight: Meet School of Dragons' quest designer Brian Yoon; Cultural and civic engagement; Insider insight: Meet the subject matter expert, historian Dr Robert Batchelor; Exercises and recommended readings; Insider insight: Lucien Vatell is building an education ecosystem; 9 GAMIFIED SYSTEM DESIGN FOR MARKETING AND ENTERTAINMENT; The marketing mix; Brand building; Driven by strategy; Insider insight: CP+B's Harold Jones on gamifying Domino's Pizza; Building revenue and driving product sales; The role of big data; GS design for customer relationship management…”

Tabla de Contenidos: “…; Scarcity; Henry Ford's Assembly Line for Manufacturing Cars; Cultured Pearls; Information and the Coming Era of Big Data…”