A step-by-step approach to building stunning dashboards with QlikViewKey FeaturesPerform effective storytelling through interactive dashboards built with QlikViewCreate different types of visualizations from a variety of data sourcesIncludes tips, tricks, and best practices to perform effective Business Intelligence using QlikViewBook DescriptionQlikView is one of the market leaders when it comes to building effective Business Intelligence solutions.
Pattern recognition is a fast growing area with applications in a widely diverse number of fields such as communications engineering, bioinformatics, data mining, content-based database retrieval, to name but a few.
Integrate scikit-learn with various tools such as NumPy, pandas, imbalanced-learn, and scikit-surprise and use it to solve real-world machine learning problemsKey FeaturesDelve into machine learning with this comprehensive guide to scikit-learn and scientific PythonMaster the art of data-driven problem-solving with hands-on examplesFoster your theoretical and practical knowledge of supervised and unsupervised machine learning algorithmsBook DescriptionMachine learning is applied everywhere, from business to research and academia, while scikit-learn is a versatile library that is popular among machine learning practitioners.
Cultivating Professional Identity in Design is a nuanced, comprehensive companion for designers across disciplines honing their identities, self-perception, personal strengths, and essential attributes.
Stochastic Modeling and Statistical Methods: Advances and Applications is the practical guide to the latest developments in data analysis and research methods.
Explore Kinesis managed services such as Kinesis Data Streams, Kinesis Data Analytics, Kinesis Data Firehose, and Kinesis Video Streams with the help of practical use casesKey FeaturesGet well versed with the capabilities of Amazon KinesisExplore the monitoring, scaling, security, and deployment patterns of various Amazon Kinesis servicesLearn how other Amazon Web Services and third-party applications such as Splunk can be used as destinations for Kinesis dataBook DescriptionAmazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services.
Modeling and Control of Drug Delivery Systems provides comprehensive coverage of various drug delivery and targeting systems and their state-of-the-art related works, ranging from theory to real-world deployment and future perspectives.
Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences.
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.
Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and moreKey FeaturesMaster machine learning, deep learning, and predictive modeling concepts in R 3.
Tackle the complex challenges faced while building end-to-end deep learning models using modern R librariesKey FeaturesUnderstand the intricacies of R deep learning packages to perform a range of deep learning tasksImplement deep learning techniques and algorithms for real-world use casesExplore various state-of-the-art techniques for fine-tuning neural network modelsBook DescriptionDeep learning (DL) has evolved in recent years with developments such as generative adversarial networks (GANs), variational autoencoders (VAEs), and deep reinforcement learning.
This book discusses the multifaceted nature of organizational excellence and proceeds to consider the roles played by data, technological advances leading to innovation and value-based leadership in guiding an organization in its journey towards excellence.
Data Scientists are experts at analyzing, modelling and visualizing data but, at one point or another, have all encountered difficulties in collaborating with or delivering their work to the people and systems that matter.
Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods.
Although, the basic concept of a fuel cell is quite simple, creating new designs and optimizing their performance takes serious work and a mastery of several technical areas.
With the aim of simplifying relational database modeling, Database Modeling Step-by-Step presents the standard approach to database normalization and then adds its own approach, which is a more simplistic, intuitive way to building relational database models.
For many small businesses, organisations, clubs, artists, faith groups, voluntary organisations/charities and sole traders, applying the General Data Protection Regulation (GDPR) has been like playing a game of "e;Snakes and Ladders"e;.
Get up and running with machine learning life cycle management and implement MLOps in your organizationKey FeaturesBecome well-versed with MLOps techniques to monitor the quality of machine learning models in productionExplore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed modelsPerform CI/CD to automate new implementations in ML pipelinesBook DescriptionEngineering MLps presents comprehensive insights into MLOps coupled with real-world examples in Azure to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production.
Resource Description Framework (or RDF, in short) is set to deliver many of the original semi-structured data promises: flexible structure, optional schema, and rich, flexible Universal Resource Identifiers as a basis for information sharing.
The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements.
Master Oracle SOA Suite 12cDesign, implement, manage, and maintain a highly flexible service-oriented computing infrastructure across your enterprise using the detailed information in this Oracle Press guide.
Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges.
Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videosKey FeaturesImplement image classification and object detection using machine learning and deep learningPerform image classification, object detection, image segmentation, and other Computer Vision tasksCrisp content with a practical approach to solving real-world problems in Computer VisionBook DescriptionPython is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries.
Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learningKey FeaturesGet up and running with graph analytics with the help of real-world examplesExplore various use cases such as fraud detection, graph-based search, and recommendation systemsGet to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scalingBook DescriptionNeo4j is a graph database that includes plugins to run complex graph algorithms.
Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applicationsKey FeaturesDiscover the new features introduced in Elasticsearch 7Explore techniques for distributed search, indexing, and clusteringGain hands-on knowledge of implementing Elasticsearch for your enterpriseBook DescriptionElasticsearch is one of the most popular tools for distributed search and analytics.
Provides a one-stop resource for engineers learning biostatistics using MATLAB and WinBUGS Through its scope and depth of coverage, this book addresses the needs of the vibrant and rapidly growing bio-oriented engineering fields while implementing software packages that are familiar to engineers.
Create dynamic dashboards to perform interactive analytics for business intelligence operationsKey FeaturesExplore newly added features in Qlik SenseDiscover best practices to work with data using Qlik SenseLearn to implement advanced functions for better data insightBook DescriptionQlik Sense allows you to explore simple and complex data to reveal hidden insight and data relationships that help you make quality decisions for overall productivity.
A concise guide to the theory and application of numerical methods for predicting ocean acoustic propagation, also providing an introduction to numerical methods, with an overview of those methods presently in use.
New computational design tools have evolved rapidly and been increasingly applied in the field of design in recent years, complimenting and even replacing the traditional design media and approaches.
Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant.
Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and librariesKey FeaturesLearn, develop, and deploy advanced reinforcement learning algorithms to solve a variety of tasksUnderstand and develop model-free and model-based algorithms for building self-learning agentsWork with advanced Reinforcement Learning concepts and algorithms such as imitation learning and evolution strategiesBook DescriptionReinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements.
