Materias: “…Materials science…”

Materias: “…National Science Foundation (U.S.)…”

Materias: “…Computer science…”

“…It has been many decades, since Computer Science has been able to achieve tremendous recognition and has been applied in various fields, mainly computer programming and software engineering. …”

Tabla de Contenidos: “…Science communication in democratic knowledge societies -- Science as "universal light" -- The elusive concept of the modern public -- The elusive concept of modern politics -- A political category of science communication…”

Materias:

Tabla de Contenidos: “…Front Cover; The Science and Technology of Counterterrorism: Measuring Physical and Electronic Security Risk; Copyright; Dedication; Contents; Acknowledgments; About the Author; Preface; Part I: Modeling Terrorism Risk; Chapter 1: Terrorism Threats, Risk, and Risk Assessments; 1.1. …”

Tabla de Contenidos: “…Front Cover; Table of contents; Preface; Conference Committees; Computer and information sciences; A framework for mobile microrobots control; A novel wideband band-stop filter based on SRR DGS; Research on the transmission enhancement properties of a novel subwavelength grating structure and mechanism; A compensated three-stages sharpened comb decimation filter; A recommendation algorithm for multiple e-commerce sites; Neural network ensembles using regularized negative correlation learning for classification with imbalanced data…”

“…It has long been recognized that science is the pursuit of knowledge, knowledge is power, and power is political. …”

Tabla de Contenidos: “…Chapter 1: Data Science Technology Stack -- Chapter 2: Vermeulen - Krennwallner - Hillman - Clark -- Chapter 3: Layered Framework -- Chapter 4: Business Layer -- Chapter 5: Utility Layer -- Chapter 6: Three Management Layers -- Chapter 7: Retrieve Super Step -- Chapter 8: Assess Super Step -- Chapter 9: Process Super Step -- Chapter 10: Transform Super Step -- Chapter 11: Organize and Report Super Step -- …”

“…Data science unifies statistics, data analysis and machine learning to achieve a better understanding of the masses of data which are produced today, and to improve prediction. …”

“…It is aimed at those who want to kick-start their careers in data science by quickly learning data science techniques without going through all the mathematics behind machine learning algorithms. …”

Tabla de Contenidos: “…Cover -- Praise For This Book -- Title Page -- Copyright -- About the Authors -- Acknowledgments -- Contents at a Glance -- Contents -- Foreword for Smarter Data Science -- Epigraph -- Preamble -- Chapter 1 Climbing the AI Ladder -- Readying Data for AI -- Technology Focus Areas -- Taking the Ladder Rung by Rung -- Constantly Adapt to Retain Organizational Relevance -- Data-Based Reasoning Is Part and Parcel in the Modern Business -- Toward the AI-Centric Organization -- Summary -- Chapter 2 Framing Part I: Considerations for Organizations Using AI -- Data-Driven Decision-Making; Using Interrogatives to Gain Insight -- The Trust Matrix -- The Importance of Metrics and Human Insight -- Democratizing Data and Data Science -- Aye, a Prerequisite: Organizing Data Must Be a Forethought -- Preventing Design Pitfalls -- Facilitating the Winds of Change: How Organized Data Facilitates Reaction Time -- Quae Quaestio (Question Everything) -- Summary -- Chapter 3 Framing Part II: Considerations for Working with Data and AI -- Personalizing the Data Experience for Every User -- Context Counts: Choosing the Right Way to Display Data; Ethnography: Improving Understanding Through Specialized Data -- Data Governance and Data Quality -- The Value of Decomposing Data -- Providing Structure Through Data Governance -- Curating Data for Training -- Additional Considerations for Creating Value -- Ontologies: A Means for Encapsulating Knowledge -- Fairness, Trust, and Transparency in AI Outcomes -- Accessible, Accurate, Curated, and Organized -- Summary -- Chapter 4 A Look Back on Analytics: More Than One Hammer -- Been Here Before: Reviewing the Enterprise Data Warehouse -- Drawbacks of the Traditional Data Warehouse -- Paradigm Shift; Modern Analytical Environments: The Data Lake -- By Contrast -- Indigenous Data -- Attributes of Difference -- Elements of the Data Lake -- The New Normal: Big Data Is Now Normal Data -- Liberation from the Rigidity of a Single Data Model -- Streaming Data -- Suitable Tools for the Task -- Easier Accessibility -- Reducing Costs -- Scalability -- Data Management and Data Governance for AI -- Schema-on-Read vs. …”

“…The vast majority of word of mouth happens offline, in everyday conversations. In The Science of Customer Connections, Karrh offers simple concepts plus practical guidance for individual professionals, teams, and complex organizations to be part of those conversations in ways that grow their business. …”

“…With a step-by-step introduction to new concepts, this Django course will gradually help you get to grips with the essentials of data science…”

“…Python for the Life Sciences provides the tools, confidence and inspiration to start crafting your own Python solutions for the challenges you face in your research. …”

“…Key Features Explore the depths of data science, from data collection through to visualization Learn pandas, scikit-learn, and Matplotlib in detail Study various data science algorithms using real-world datasets Book Description Data Science with Python begins by introducing you to data science and teaches you to install the packages you need to create a data science coding environment. …”