Data mining

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical.

Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics.

Social computing concerns the study of social behavior and context based on computational systems.

The use of geospatial technologies has become ubiquitous since the leading Internet vendors delivered a number of popular map websites.

Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty.

There can be no question, my dear Watson, of the value of exercise before breakfast.

Data mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns.

Most commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics.

The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering.

This book is about using interactive and dynamic plots on a computer screen as part of data exploration and modeling, both alone and as a partner with static graphics and non-graphical computational methods.

Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes.

The breakthrough idea of parallel coordinates has enchanted many people with its cleverness and power.

Data warehousing and data mining provide techniques for collecting information from distributed databases and for performing data analysis.

Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams.

Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets.

Graphics are great for exploring data, but how can they be used for looking at the large datasets that are commonplace to-day?

"e;If you torture the data long enough, Nature will confess,"e; said 1991 Nobel-winning economist Ronald Coase.

Data mining is a mature technology.

Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data.

Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository.

Knowledge, hidden in voluminous data repositories routinely created and maintained by today's applications, can be extracted by data mining.

In many applications, e.

While SAS and SPSS have many things in common, R is very different.

Conceptually, a database consists of objects and relationships.

Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way.

Information and communication technology and the Internet of Things play key roles in smart city projects.

Learn to develop blockchain-based distributed ledgers and deploy a Hyperledger Fabric network with concrete exercises and examplesKey FeaturesUpdated with the latest features and additions that come with Hyperledger Fabric 2Write your own smart contracts and services using Java and JavaScript on a Hyperledger Fabric networkDive into real-world blockchain challenges such as integration and scalabilityBook DescriptionBlockchain with Hyperledger Fabric - Second Edition is a refreshed and extended version of the successful book on practical Hyperledger Fabric blockchain development.

A comprehensive guide to building, managing, and securing scalable and reliable database and data warehousing applications using Postgres 12 and 13Key FeaturesSet up your database cluster and monitor, secure, and fine-tune it for optimal performanceLearn the fundamentals of database management and implement client- and server-side programming using SQL and PL/pgSQLExplore useful tips to develop efficient PostgreSQL database solutions from scratchBook DescriptionPostgreSQL is one of the fastest-growing open source object-relational database management systems (DBMS) in the world.

Presenting innovative research-oriented ideas, and the implementation and socioeconomic applications of internet of things-based network, Challenges and Solutions in Internet of Things-Based Smart Applications showcases smart waste management, optical technologies for internet of things and remote patient monitoring and data analysis.

Presenting innovative research-oriented ideas, and the implementation and socioeconomic applications of internet of things-based network, Challenges and Solutions in Internet of Things-Based Smart Applications showcases smart waste management, optical technologies for internet of things and remote patient monitoring and data analysis.

Learn quick and effective techniques for developing blockchain-based distributed ledgers with easeKey FeaturesDiscover why blockchain is a game changer in the technology landscapeSet up blockchain networks using Hyperledger FabricWrite smart contracts at speed with Hyperledger ComposerBook DescriptionBlockchain and Hyperledger are open source technologies that power the development of decentralized applications.

The missing expert-led manual for the AWS ecosystem - go from foundations to building data engineering pipelines effortlesslyPurchase of the print or Kindle book includes a free eBook in the PDF format.

Get hands-on with deploying and managing your database services to provide scalable and high-speed data access on CockroachDBKey FeaturesGain insights into CockroachDB and build highly reliable cloud-native applicationsExplore the power of a scalable and highly available cloud-native SQL database to distribute data and workloads automaticallyBuild high-speed database services using CockroachDB and troubleshoot performance issuesBook DescriptionGetting Started with CockroachDB will introduce you to the inner workings of CockroachDB and help you to understand how it provides faster access to distributed data through a SQL interface.

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.

Discover how to describe your data in detail, identify data issues, and find out how to solve them using commonly used techniques and tips and tricksKey FeaturesGet well-versed with various data cleaning techniques to reveal key insightsManipulate data of different complexities to shape them into the right form as per your business needsClean, monitor, and validate large data volumes to diagnose problems before moving on to data analysisBook DescriptionGetting clean data to reveal insights is essential, as directly jumping into data analysis without proper data cleaning may lead to incorrect results.

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.

Transform Big Data into Insight"e;In this book, some of Oracle's best engineers and architects explain how you can make use of big data.

Discover the power of location data to build effective, intelligent data models with Geospatial ecosystemsKey FeaturesManipulate location-based data and create intelligent geospatial data modelsBuild effective location recommendation systems used by popular companies such as UberA hands-on guide to help you consume spatial data and parallelize GIS operations effectivelyBook DescriptionData scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models.

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.

Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandasKey FeaturesUse powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial dataExplore unique recipes for financial data analysis and processing with PythonEstimate popular financial models such as CAPM and GARCH using a problem-solution approachBook DescriptionPython is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries.

Get to grips with pandas-a versatile and high-performance Python library for data manipulation, analysis, and discoveryKey FeaturesPerform efficient data analysis and manipulation tasks using pandasApply pandas to different real-world domains using step-by-step demonstrationsGet accustomed to using pandas as an effective data exploration toolBook DescriptionData analysis has become a necessary skill in a variety of positions where knowing how to work with data and extract insights can generate significant value.

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

Collect and scrape different complexities of data from the modern Web using the latest tools, best practices, and techniques Key FeaturesLearn different scraping techniques using a range of Python libraries such as Scrapy and Beautiful SoupBuild scrapers and crawlers to extract relevant information from the webAutomate web scraping operations to bridge the accuracy gap and manage complex business needsBook DescriptionWeb scraping is an essential technique used in many organizations to gather valuable data from web pages.

A one-of-a-kind guide to setting up a malware research lab, using cutting-edge analysis tools, and reporting the findingsAdvanced Malware Analysis is a critical resource for every information security professional's anti-malware arsenal.

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.

Combine advanced analytics including Machine Learning, Deep Learning Neural Networks and Natural Language Processing with modern scalable technologies including Apache Spark to derive actionable insights from Big Data in real-timeKey FeaturesMake a hands-on start in the fields of Big Data, Distributed Technologies and Machine LearningLearn how to design, develop and interpret the results of common Machine Learning algorithmsUncover hidden patterns in your data in order to derive real actionable insights and business valueBook DescriptionEvery person and every organization in the world manages data, whether they realize it or not.

Master scala's advanced techniques to solve real-world problems in data analysis and gain valuable insights from your dataKey FeaturesA beginner's guide for performing data analysis loaded with numerous rich, practical examplesAccess to popular Scala libraries such as Breeze, Saddle for efficient data manipulation and exploratory analysisDevelop applications in Scala for real-time analysis and machine learning in Apache SparkBook DescriptionEfficient business decisions with an accurate sense of business data helps in delivering better performance across products and services.