Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry.
This book presents how federated learning helps to understand and learn from user activity in Internet of Things (IoT) applications while protecting user privacy.
This book provides a principled data-driven framework that progressively constructs, enriches, and applies taxonomies without leveraging massive human annotated data.
Build and deploy your own data pipelines on GCP, make key architectural decisions, and gain the confidence to boost your career as a data engineerKey FeaturesUnderstand data engineering concepts, the role of a data engineer, and the benefits of using GCP for building your solutionLearn how to use the various GCP products to ingest, consume, and transform data and orchestrate pipelinesDiscover tips to prepare for and pass the Professional Data Engineer examBook DescriptionWith this book, you'll understand how the highly scalable Google Cloud Platform (GCP) enables data engineers to create end-to-end data pipelines right from storing and processing data and workflow orchestration to presenting data through visualization dashboards.
Use the Elastic Stack for search, security, and observability-related use cases while working with large amounts of data on-premise and on the cloudKey FeaturesLearn the core components of the Elastic Stack and how they work togetherBuild search experiences, monitor and observe your environments, and defend your organization from cyber attacksGet to grips with common architecture patterns and best practices for successfully deploying the Elastic StackBook DescriptionThe Elastic Stack helps you work with massive volumes of data to power use cases in the search, observability, and security solution areas.
Over the last decade, there has been a growing interest in human behavior analysis, motivated by societal needs such as security, natural interfaces, affective computing, and assisted living.
Focusing on students' presentations and discussions in laboratory seminars, this book presents case studies on evidence-based education using artificial intelligence (AI) technologies.
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021.
The multi-volume set LNAI 12975 until 12979 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2021, which was held during September 13-17, 2021.
The two-volume set LNAI 11431 and 11432 constitutes the refereed proceedings of the 11th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2019, held in Yogyakarta, Indonesia, in April 2019.
The two-volume set LNAI 11431 and 11432 constitutes the refereed proceedings of the 11th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2019, held in Yogyakarta, Indonesia, in April 2019.
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications.
Extract accurate information from data to train and improve machine learning models using NumPy, SciPy, pandas, and scikit-learn librariesKey FeaturesDiscover solutions for feature generation, feature extraction, and feature selectionUncover the end-to-end feature engineering process across continuous, discrete, and unstructured datasetsImplement modern feature extraction techniques using Python's pandas, scikit-learn, SciPy and NumPy librariesBook DescriptionFeature engineering is invaluable for developing and enriching your machine learning models.
Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbookKey Features[*] Your quick guide to implementing TensorFlow in your day-to-day machine learning activities[*] Learn advanced techniques that bring more accuracy and speed to machine learning[*] Upgrade your knowledge to the second generation of machine learning with this guide on TensorFlowBook DescriptionTensorFlow is an open source software library for Machine Intelligence.
Acquire and analyze data from all corners of the social web with PythonKey Features[*] Make sense of highly unstructured social media data with the help of the insightful use cases provided in this guide[*] Use this easy-to-follow, step-by-step guide to apply analytics to complicated and messy social data[*] This is your one-stop solution to fetching, storing, analyzing, and visualizing social media dataBook DescriptionYour social media is filled with a wealth of hidden data - unlock it with the power of Python.
Simplify machine learning model implementations with SparkAbout This BookSolve the day-to-day problems of data science with SparkThis unique cookbook consists of exciting and intuitive numerical recipesOptimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your dataWho This Book Is ForThis book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark.
This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software.
In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses.
This book constitutes revised papers from the International Workshops held at the 18th International Conference on Business Process Management, BPM 2020, during September 13-18, 2020.
This book, endorsed by EuSoMII, provides clinicians, researchers and scientists a useful handbook to navigate the intricate landscape of data harmonization, as we embark on a journey to improve the reproducibility, robustness and generalizability of multi-centric real-world data radiomic studies.
This book, endorsed by EuSoMII, provides clinicians, researchers and scientists a useful handbook to navigate the intricate landscape of data harmonization, as we embark on a journey to improve the reproducibility, robustness and generalizability of multi-centric real-world data radiomic studies.
This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Quebec City, QC, Canada, in September 2017.
In recent years, extensive research has been conducted by eminent mathematicians and engineers whose results and proposed problems are presented in this new volume.
This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making.
This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples.
This two-volume set of LNCS 11871 and 11872 constitutes the thoroughly refereed conference proceedings of the 20th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2019, held in Manchester, UK, in November 2019.
The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018.
This two-volume set constitutes the refereed proceedings of the workshops which complemented the 19th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in Wurzburg, Germany, in September 2019.
This book focuses in detail on data science and data analysis and emphasizes the importance of data engineering and data management in the design of big data applications.
This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.
This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.
Most businesses today are embracing digital transformation and automation, deploying the processes of data analytics in combination with advanced technologies for customer retention using such techniques as marketing automation, digital marketing, machine learning (ML), blockchain, generative AI, and robotics.
Revamp your data landscape and implement highly effective data pipelines in AWS with this hands-on guidePurchase of the print or Kindle book includes a free PDF eBookKey FeaturesExecute extract, transform, and load (ETL) tasks on data lakes, data warehouses, and databasesImplement effective Pandas data operation with data wranglerIntegrate pipelines with AWS data servicesBook DescriptionData wrangling is the process of cleaning, transforming, and organizing raw, messy, or unstructured data into a structured format.
