Data capture and analysis

The statistical analyses that students of the life-sciences are being expected to perform are becoming increasingly advanced.

Experiments, surveys, measurements, and observations all generate data.

The social sciences are becoming datafied.

The social sciences are becoming datafied.

Demography is everywhere in our lives: from birth to death.

Statistical methods are a key tool for all scientists working with data, but learning the basics continues to challenge successive generations of students.

Discover expert techniques for combining machine learning with the analytic capabilities of Elastic Stack and uncover actionable insights from your dataKey FeaturesIntegrate machine learning with distributed search and analyticsPreprocess and analyze large volumes of search data effortlesslyOperationalize machine learning in a scalable, production-worthy wayBook DescriptionElastic Stack, previously known as the ELK stack, is a log analysis solution that helps users ingest, process, and analyze search data effectively.

Speed up the design and implementation of deep learning solutions using Apache SparkKey FeaturesExplore the world of distributed deep learning with Apache SparkTrain neural networks with deep learning libraries such as BigDL and TensorFlowDevelop Spark deep learning applications to intelligently handle large and complex datasetsBook DescriptionDeep learning is a subset of machine learning where datasets with several layers of complexity can be processed.

Analytics is the application of mathematical and statistical concepts to large data sets so as to distil insights that offer the owner some options for action and competitive advantage or value.

Analytics is the application of mathematical and statistical concepts to large data sets so as to distil insights that offer the owner some options for action and competitive advantage or value.

This book focuses on the recent rise of "e;infodemics"e; as forms of disinformation, misinformation and mal-information saturate contemporary media platforms, shaping public opinion to advance agendas.

This book focuses on the recent rise of "e;infodemics"e; as forms of disinformation, misinformation and mal-information saturate contemporary media platforms, shaping public opinion to advance agendas.

Next-generation DNA and RNA sequencing has revolutionized biology and medicine.

The second edition of this internationally acclaimed title is the ideal handbook for those involved in conducting epidemiological research.

Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting.

Become an expert at using Python for advanced statistical analysis of data using real-world examplesKey Features[*] Clean, format, and explore data using graphical and numerical summaries[*] Leverage the IPython environment to efficiently analyze data with Python[*] Packed with easy-to-follow examples to develop advanced computational skills for the analysis of complex dataBook DescriptionPython, a multi-paradigm programming language, has become the language of choice for data scientists for data analysis, visualization, and machine learning.

Learn how to bring your data to life with this hands-on guide to visual analytics with TableauKey FeaturesMaster the fundamentals of Tableau Desktop and Tableau PrepLearn how to explore, analyze, and present data to provide business insightsBuild your experience and confidence with hands-on exercises and activitiesBook DescriptionLearning Tableau has never been easier, thanks to this practical introduction to storytelling with data.

Learn how to make the right decisions for your business with the help of Python recipes and the expertise of data leadersKey FeaturesLearn and practice various clustering techniques to gather market insights Explore real-life use cases from the business world to contextualize your learningWork your way through practical recipes that will reinforce what you have learnedBook DescriptionOne of the most valuable contributions of data science is toward helping businesses make the right decisions.

Meeting the Challenges of Data Quality Management outlines the foundational concepts of data quality management and its challenges.

Data stewards in any organization are the backbone of a successful data governance implementation because they do the work to make data trusted, dependable, and high quality.

Take your Python text processing skills to another level by learning about the latest natural language processing and machine learning techniques with this full color guideKey FeaturesLearn how to acquire and process textual data and visualize the key findingsObtain deeper insight into the most commonly used algorithms and techniques and understand their tradeoffsImplement models for solving real-world problems and evaluate their performanceBook DescriptionWith the ever-increasing demand for machine learning and programming professionals, it's prime time to invest in the field.

E-health applications such as tele-medicine, tele-radiology, tele-ophthalmology, and tele-diagnosis are very promising and have immense potential to improve global healthcare.

Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data.

Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization.

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data.

Learn the basics of Data Science through an easy to understand conceptual framework and immediately practice using RapidMiner platform.

Meta-Analytics: Consensus Approaches and System Patterns for Data Analysis presents an exhaustive set of patterns for data science to use on any machine learning based data analysis task.

Simplify your ETL processes with these hands-on data hygiene tips, tricks, and best practices.

Leverage the power of Python and statistical modeling techniques for building accurate predictive modelsKey FeaturesGet introduced to Python's rich suite of libraries for statistical modelingImplement regression, clustering and train neural networks from scratchIncludes real-world examples on training end-to-end machine learning systems in PythonBook DescriptionPython's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today.

Leverage the power of the Python data science libraries and advanced machine learning techniques to analyse large unstructured datasets and predict the occurrence of a particular future event.

Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and KubernetesKey FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book DescriptionThe increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models.

Build a strong foundation of machine learning algorithms in 7 daysKey FeaturesUse Python and its wide array of machine learning libraries to build predictive models Learn the basics of the 7 most widely used machine learning algorithms within a weekKnow when and where to apply data science algorithms using this guideBook DescriptionMachine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data.

Explore distributed ledger technology, decentralization, and smart contracts and develop real-time decentralized applications with Ethereum and SolidityKey FeaturesGet to grips with the underlying technical principles and implementations of blockchainBuild powerful applications using Ethereum to secure transactions and create smart contractsGain advanced insights into cryptography and cryptocurrenciesBook DescriptionBlockchain technology is a distributed ledger with applications in industries such as finance, government, and media.

Solve real-world statistical problems using the most popular R packages and techniquesKey FeaturesLearn how to apply statistical methods to your everyday research with handy recipesFoster your analytical skills and interpret research across industries and business verticalsPerform t-tests, chi-squared tests, and regression analysis using modern statistical techniquesBook DescriptionR is a popular programming language for developing statistical software.

Progressively explore UI development with Shiny via practical examplesKey FeaturesWrite a Shiny interface in pure HTMLExplore powerful layout functions to make attractive dashboards and other intuitive interfacesGet to grips with Bootstrap and leverage it in your Shiny applicationsBook DescriptionAlthough vanilla Shiny applications look attractive with some layout flexibility, you may still want to have more control over how the interface is laid out to produce a dashboard.

Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applicationsKey FeaturesBuild independent machine learning (ML) systems leveraging the best features of R 3.

Get unique insights from your data by combining the power of SQL Server, R and PythonKey FeaturesUse the features of SQL Server 2017 to implement the data science project life cycleLeverage the power of R and Python to design and develop efficient data modelsfind unique insights from your data with powerful techniques for data preprocessing and analysisBook DescriptionSQL Server only started to fully support data science with its two most recent editions.

Implement real-world decentralized applications using Python, Vyper, Populus, and EthereumKey FeaturesStay up-to-date with everything you need to know about the blockchain ecosystemImplement smart contracts, wallets, and decentralized applications(DApps) using Python librariesGet deeper insights into storing content in a distributed storage platformBook DescriptionBlockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions.

Advances in Imaging and Electron Physics, Volume 203, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy.

Big Data and Smart Service Systems presents the theories and applications regarding Big Data and smart service systems, data acquisition, smart cities, business decision-making support, and smart service design.

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications.

OCEB 2 Certification Guide, Second Edition has been updated to cover the new version 2 of the BPMN standard and delivers expert insight into BPM from one of the developers of the OCEB Fundamental exam, offering full coverage of the fundamental exam material for both the business and technical tracks to further certification.

Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability.

Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data.

Building the Agile Enterprise with Capabilities, Collaborations and Values, Second Edition covers advances that make technology more powerful and pervasive while, at the same time, improving alignment of technology with business.

Data mapping in a data warehouse is the process of creating a link between two distinct data models' (source and target) tables/attributes.

Cyber Security Awareness for Corporate Directors and Board Members is a concise overview of the cyber threat to you, your business, your livelihood, and what you need to do--especially as board members and directors of boards-- to lower the risk, reduce or eliminate liability, and protect reputation.

Cyber Security for CEOs and Managment is a concise overview of the security threats posed to organizations and networks by the ubiquity of USB Flash Drives used as storage devices.

The WWW era made billions of people dramatically dependent on the progress of data technologies, out of which Internet search and Big Data are arguably the most notable.

Application Performance Management (APM) in the Digital Enterprise enables IT professionals to be more successful in managing their company's applications.