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Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results. Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included. Topics and features: Guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring Includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix Provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms Integrates illustrations and case-study-style examples to support pedagogical exposition Supplies further tools and information at an associated website This practical and systematic textbook/reference is a “need-to-have” tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a “need to use, need to keep” resource following one's exploration of the subject. Prof. Dr. Michael R. Berthold is Professor for Bioinformatics and Information Mining at the University of Konstanz. Prof. Dr. Christian Borgelt is Professor for Data Science at the Paris Lodron University of Salzburg. Prof. Dr. Frank Höppner is Professor of Information Engineering at Ostfalia University of Applied Sciences. Prof. Dr. Frank Klawonn is Professor for Data Analysis and Pattern Recognition at the same institution and head of the Biostatistics Group at the Helmholtz Centre for Infection Research. Dr. Rosaria Silipo is a Principal Data Scientist and Head of Evangelism at KNIME AG.

Data mining. --- Machine learning. --- Big data. --- Data Mining and Knowledge Discovery. --- Machine Learning. --- Big Data/Analytics. --- Data sets, Large --- Large data sets --- Data sets --- Learning, Machine --- Artificial intelligence --- Machine theory --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Artificial intelligence.

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Life sciences. --- Information storage and retrieval systems. --- Medical informatics. --- Database management. --- Application software. --- Proteins. --- Life Sciences. --- Information Storage and Retrieval. --- Health Informatics. --- Database Management. --- Computer and Information Systems Applications. --- Protein Biochemistry. --- Life sciences --- Bioinformatics --- Computational biology --- Molecular biology --- Data processing

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Life sciences. --- Information storage and retrieval systems. --- Medical informatics. --- Database management. --- Application software. --- Proteins. --- Life Sciences. --- Information Storage and Retrieval. --- Health Informatics. --- Database Management. --- Computer and Information Systems Applications. --- Protein Biochemistry. --- Life sciences --- Bioinformatics --- Computational biology --- Molecular biology --- Data processing

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Computational Biology --- Life sciences --- Bioinformatics --- Computational biology --- Molecular biology --- Sciences de la vie --- Bio-informatique --- Biologie moléculaire --- Congresses. --- Data processing --- Informatique --- Congrès --- Congresses --- Genomics --- Publication Formats --- Biology --- Genetics --- Biological Science Disciplines --- Publication Characteristics --- Natural Science Disciplines --- Disciplines and Occupations --- Computer Science --- Biology - General --- Engineering & Applied Sciences --- Health & Biological Sciences --- Biosciences --- Sciences, Life --- Life sciences. --- Health informatics. --- Computers. --- Database management. --- Information storage and retrieval. --- Life Sciences. --- Life Sciences, general. --- Theory of Computation. --- Information Storage and Retrieval. --- Health Informatics. --- Database Management. --- Information Systems Applications (incl. Internet). --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Machine theory --- Calculators --- Cyberspace --- Clinical informatics --- Health informatics --- Medical information science --- Information science --- Medicine --- Science --- Information theory. --- Information storage and retrieva. --- Medical records --- Data processing. --- EHR systems --- EHR technology --- EHRs (Electronic health records) --- Electronic health records --- Electronic medical records --- EMR systems --- EMRs (Electronic medical records) --- Information storage and retrieval systems --- Communication theory --- Communication --- Medical care --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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This book constitutes the refereed proceedings of the Second International Symposium on Intelligent Data Analysis, IDA-97, held in London, UK, in August 1997.The volume presents 50 revised full papers selected from a total of 107 submissions. Also included is a keynote, Intelligent Data Analysis: Issues and Opportunities, by David J. Hand. The papers are organized in sections on exploratory data analysis, preprocessing and tools; classification and feature selection; medical applications; soft computing; knowledge discovery and data mining; estimation and clustering; data quality; qualitative models.

Mathematical Statistics --- Expert Systems (Computer Science) --- Computer Science --- Mathematics --- Computers --- Mathematical statistics --- Expert systems (Computer science) --- Data processing