Learn to extract actionable insights from your big data in real time using a range of Microsoft Azure featuresKey FeaturesUpdated with the latest features and new additions to Microsoft AzureMaster the fundamentals of cloud analytics using AzureLearn to use Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse) to derive real-time customer insightsBook DescriptionCloud Analytics with Microsoft Azure serves as a comprehensive guide for big data analysis and processing using a range of Microsoft Azure features.
Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organizationKey FeaturesLearn the basics of data science and explore its possibilities and limitationsManage data science projects and assemble teams effectively even in the most challenging situationsUnderstand management principles and approaches for data science projects to streamline the innovation processBook DescriptionData science and machine learning can transform any organization and unlock new opportunities.
Learn to construct state-of-the-art simulation models with Python and enhance your simulation modelling skills, as well as create and analyze digital prototypes of physical models with easeKey FeaturesUnderstand various statistical and physical simulations to improve systems using PythonLearn to create the numerical prototype of a real model using hands-on examplesEvaluate performance and output results based on how the prototype would work in the real worldBook DescriptionSimulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it.
A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis.
Microsoft Power BI is a data analytics and visualization tool powerful enough for the most demanding data scientists, but accessible enough for everyday use for anyone who needs to get more from data.
Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key FeaturesA step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZA modern, practical and computational approach to Bayesian statistical modelingA tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises.
Build powerful data analytics applications with this business intelligence tool and overcome all your business challengesKey FeaturesMaster time-saving techniques and make your QlikView development more efficientPerform geographical analysis and sentiment analysis in your QlikView applicationsExplore advanced QlikView techniques, tips, and tricks to deliver complex business requirementsBook DescriptionQlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand.
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.
Enter the exciting world of Julia, a high-performance language for technical computingKey FeaturesLeverage Julia's high speed and efficiency for your applicationsWork with Julia in a multi-core, distributed, and networked environmentApply Julia to tackle problems concurrently and in a distributed environmentBook DescriptionThe release of Julia 1.
Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud.
A complete guide to understanding, developing, and testing popular security-token smart contractsKey FeaturesUnderstand key Blockchain and Ethereum platforms conceptsStep-by-step guide to developing STO smart contracts on EthereumMonetize digital tokens under various U.
Learn how to quickly generate business intelligence, insights and create interactive dashboards for digital storytelling through various data sources with RedashKey FeaturesLearn the best use of visualizations to build powerful interactive dashboardsCreate and share visualizations and data in your organizationWork with different complexities of data from different data sourcesBook DescriptionData exploration and visualization is vital to Business Intelligence, the backbone of almost every enterprise or organization.
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.
This new volume addresses the growing interest in and use of big data analytics in many industries and in many research fields around the globe; it is a comprehensive resource on the core concepts of big data analytics and the tools, techniques, and methodologies.
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.
Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming languageKey FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook DescriptionUnleash the power of data to reach your marketing goals with this practical guide to data science for business.
Finding Data Anomalies You Didn't Know to Look ForAnomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets.
Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of real-world examples and datasetsKey FeaturesBecome familiar with data processing, performance measuring, and model selection using various C++ librariesImplement practical machine learning and deep learning techniques to build smart modelsDeploy machine learning models to work on mobile and embedded devicesBook DescriptionC++ can make your machine learning models run faster and more efficiently.
Learn through hands-on exercises covering a variety of topics including data connections, analytics, and dashboards to effectively prepare for the Tableau Desktop Certified Associate examKey FeaturesPrepare for the Tableau Desktop Certified Associate exam with the help of tips and techniques shared by expertsImplement Tableau's advanced analytical capabilities such as forecastingDelve into advanced Tableau features and explore best practices for building dashboardsBook DescriptionThe Tableau Desktop Certified Associate exam measures your knowledge of Tableau Desktop and your ability to work with data and data visualization techniques.
A comprehensive compilation of new developments in data linkage methodology The increasing availability of large administrative databases has led to a dramatic rise in the use of data linkage, yet the standard texts on linkage are still those which describe the seminal work from the 1950-60s, with some updates.
This book covers many helpful analysis tools and processes to assist energy managers (EMs) administer their energy program through their meter management system (MMS).
Pattern Recognition on Oriented Matroids covers a range of innovative problems in combinatorics, poset and graph theories, optimization, and number theory that constitute a far-reaching extension of the arsenal of committee methods in pattern recognition.
Build, manage, and configure high-performing, reliable NoSQL database for your applications with CassandraKey FeaturesWrite programs more efficiently using Cassandra's features with the help of examplesConfigure Cassandra and fine-tune its parameters depending on your needsIntegrate Cassandra database with Apache Spark and build strong data analytics pipelineBook DescriptionWith ever-increasing rates of data creation, the demand for storing data fast and reliably becomes a need.
The lure of big data and analytics has produced new partnerships between news media and social media and consequently a fragmentation of digital journalism.
Learn how to use R to apply powerful machine learning methods and gain insight into real-world applications using clustering, logistic regressions, random forests, support vector machine, and more.
Quickly build and deploy massive data pipelines and improve productivity using Azure DatabricksKey FeaturesGet to grips with the distributed training and deployment of machine learning and deep learning modelsLearn how ETLs are integrated with Azure Data Factory and Delta LakeExplore deep learning and machine learning models in a distributed computing infrastructureBook DescriptionMicrosoft Azure Databricks helps you to harness the power of distributed computing and apply it to create robust data pipelines, along with training and deploying machine learning and deep learning models.
Design cost-efficient database solutions, scale enterprise operations and reduce overhead business costs with MySQLKey FeaturesExplore the new and advanced features of MySQL 8.
Text As Data: Combining qualitative and quantitative algorithms within the SAS system for accurate, effective and understandable text analytics The need for powerful, accurate and increasingly automatic text analysis software in modern information technology has dramatically increased.
Build smarter systems by combining artificial intelligence and the Internet of Things-two of the most talked about topics todayKey FeaturesLeverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT dataProcess IoT data and predict outcomes in real time to build smart IoT modelsCover practical case studies on industrial IoT, smart cities, and home automationBook DescriptionThere are many applications that use data science and analytics to gain insights from terabytes of data.
