Information architecture

Over the past few years, finite-size scaling has become an increasingly important tool in studies of critical systems.

A quick start guide to visualize your Elasticsearch dataKey FeaturesYour hands-on guide to visualizing the Elasticsearch data as well as navigating the Elastic stackWork with different Kibana plugins and create effective machine learning jobs using KibanaBuild effective dashboards and reports without any hassleBook DescriptionThe Elastic Stack is growing rapidly and, day by day, additional tools are being added to make it more effective.

Implement supervised, unsupervised, and generative deep learning (DL) models using Keras and Dopamine with TensorFlowKey FeaturesUnderstand the fundamental machine learning concepts useful in deep learningLearn the underlying mathematical concepts as you implement deep learning models from scratchExplore easy-to-understand examples and use cases that will help you build a solid foundation in DLBook DescriptionWith information on the web exponentially increasing, it has become more difficult than ever to navigate through everything to find reliable content that will help you get started with deep learning.

Analysis and Control of Nonlinear Infinite Dimensional Systems

Word Problems

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.

Foundations of the Theory of Learning Systems

Your one-stop guide to blockchain technology and its business applicationsKey FeaturesAssimilate blockchain services such as Ethereum and Hyperledger to transform industrial applications Know in and out of blockchain technology to understand various business use casesUnderstand various common and not-so-common challenges faced in blockchain development Book DescriptionBlockchain for Business 2019 is a comprehensive guide that enables you to bring in various blockchain functionalities to extend your existing business models and make correct fully-informed decisions.

Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using PythonKey FeaturesBuild a strong foundation in algorithmic trading by becoming well-versed with the basics of financial marketsDemystify jargon related to understanding and placing multiple types of trading ordersDevise trading strategies and increase your odds of making a profit without human interventionBook DescriptionIf you want to find out how you can build a solid foundation in algorithmic trading using Python, this cookbook is here to help.

Bilinear Transformation Method

Differential and integral inequalities; theory and applications PART B: Functional, partial, abstract, and complex differential equations

This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips.

Generalized Recursion Theory II

Provability, Computability and Reflection

Leverage the power of Hyperledger Fabric to develop Blockchain-based distributed ledgers with ease Key FeaturesWrite your own chaincode/smart contracts using Golang on hyperledger networkBuild and deploy decentralized applications (DApps)Dive into real world blockchain challenges such as integration and scalabilityBook DescriptionBBlockchain and Hyperledger technologiesare hot topics today.

An Algebraic Approach to Non-Classical Logics

Explore the world of neural networks by building powerful deep learning models using the R ecosystemKey FeaturesGet to grips with the fundamentals of deep learning and neural networksUse R 3.

Get better insights from time-series data and become proficient in model performance analysisKey FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time series via real-world case studies on operations management, digital marketing, finance, and healthcareBook DescriptionThe Python time-series ecosystem is huge and often quite hard to get a good grasp on, especially for time-series since there are so many new libraries and new models.

Causality and Dispersion Relations

A hands-on guide for professionals to perform various data science tasks in RKey FeaturesExplore the popular R packages for data scienceUse R for efficient data mining, text analytics and feature engineeringBecome a thorough data science professional with the help of hands-on examples and use-cases in RBook DescriptionR is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world.

Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network architectures for deep learning with Python's most popular TensorFlow framework.

As legacy and other critical systems continue to migrate online, the need for continuous operation is imperative.

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.

A practical guide to programming for data acquisition and measurement - must-have info in just the right amount of depth for engineers who are not programming specialists.

Provability, Computability and Reflection

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization.

Logic Colloquium '77

Learn to use generative AI techniques to create novel text, images, audio, and even music with this practical, hands-on book.

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.

Build efficient forecasting models using traditional time series models and machine learning algorithms.

Provability, Computability and Reflection

Provides a practical overview of the most common database management tasks for those who need to manage data.

Perform advanced data manipulation tasks using pandas and become an expert data analyst.

Process large volumes of data in real-time while building high performance and robust data stream processing pipeline using the latest Apache Kafka 2.

Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using PythonKey FeaturesBuild a strong foundation in algorithmic trading by becoming well-versed with the basics of financial marketsDemystify jargon related to understanding and placing multiple types of trading ordersDevise trading strategies and increase your odds of making a profit without human interventionBook DescriptionIf you want to find out how you can build a solid foundation in algorithmic trading using Python, this cookbook is here to help.

System Identification

It is common wisdom that the U.

Kalman's elegant solution of the discrete linear estimation problem has had a major impact in academic engineering circles and in the aerospace industry.

A fascinating, insightful, and wonderfully written exploration of the document.

Provability, Computability and Reflection

Functional Analysis and Time Optimal Control

Enhance your data analysis and predictive modeling skills using popular Python toolsKey FeaturesCover all fundamental libraries for operation and manipulation of Python for data analysisImplement real-world datasets to perform predictive analytics with PythonAccess modern data analysis techniques and detailed code with scikit-learn and SciPyBook DescriptionPython is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations.

The Earth's Climate, Past and Future

Leverage Elastic Stack's machine learning features to gain valuable insight from your dataKey FeaturesCombine machine learning with the analytic capabilities of Elastic StackAnalyze large volumes of search data and gain actionable insight from themUse external analytical tools with your Elastic Stack to improve its performanceBook DescriptionMachine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting.

Learn how to architect, implement, and administer a complex Splunk Enterprise environment and extract valuable insights from business data.

Updated and revised second edition of the bestselling guide to exploring and mastering the most important algorithms for solving complex machine learning problemsKey FeaturesUpdated to include new algorithms and techniquesCode updated to Python 3.