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Biblioteca

MARC Lista (tabellare)
The accidental data scientist : big data applications and opportunities for librarians and information professionals / / Amy L. Affelt ; foreword by Thomas H. Davenport
The accidental data scientist : big data applications and opportunities for librarians and information professionals / / Amy L. Affelt ; foreword by Thomas H. Davenport
Autore Affelt Amy L. <1970->
Pubbl/distr/stampa Medford, New Jersey : , : Information Today, Inc., , 2015
Descrizione fisica 1 online resource (240 p.)
Disciplina 020.23
Soggetto topico Librarians - Effect of technological innovations on
Library science - Vocational guidance
Information science - Vocational guidance
Big data
Data libraries
Database searching
Electronic information resource literacy
Soggetto genere / forma Electronic books.
ISBN 1-57387-707-7
Classificazione 32.24
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910459694603321
Affelt Amy L. <1970->  
Medford, New Jersey : , : Information Today, Inc., , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
The accidental data scientist : big data applications and opportunities for librarians and information professionals / / Amy L. Affelt ; foreword by Thomas H. Davenport
The accidental data scientist : big data applications and opportunities for librarians and information professionals / / Amy L. Affelt ; foreword by Thomas H. Davenport
Autore Affelt Amy L. <1970->
Pubbl/distr/stampa Medford, New Jersey : , : Information Today, Inc., , 2015
Descrizione fisica 1 online resource (240 p.)
Disciplina 020.23
Soggetto topico Librarians - Effect of technological innovations on
Library science - Vocational guidance
Information science - Vocational guidance
Big data
Data libraries
Database searching
Electronic information resource literacy
ISBN 1-57387-707-7
Classificazione 32.24
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Big data : everything old is new again -- What the elves do -- The 21st century librarian's skillset : the role of big data -- Dipping a toe in the water : simple tools to get you started -- Big data applications and initiatives by industry -- Big data projects for info pros -- Big data communications framework : insights into big data mastery for information professionals -- Data scientists wanted : career opportunities in a big data world.
Record Nr. UNINA-9910787411403321
Affelt Amy L. <1970->  
Medford, New Jersey : , : Information Today, Inc., , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
The accidental data scientist : big data applications and opportunities for librarians and information professionals / / Amy L. Affelt ; foreword by Thomas H. Davenport
The accidental data scientist : big data applications and opportunities for librarians and information professionals / / Amy L. Affelt ; foreword by Thomas H. Davenport
Autore Affelt Amy L. <1970->
Pubbl/distr/stampa Medford, New Jersey : , : Information Today, Inc., , 2015
Descrizione fisica 1 online resource (240 p.)
Disciplina 020.23
Soggetto topico Librarians - Effect of technological innovations on
Library science - Vocational guidance
Information science - Vocational guidance
Big data
Data libraries
Database searching
Electronic information resource literacy
ISBN 1-57387-707-7
Classificazione 32.24
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Big data : everything old is new again -- What the elves do -- The 21st century librarian's skillset : the role of big data -- Dipping a toe in the water : simple tools to get you started -- Big data applications and initiatives by industry -- Big data projects for info pros -- Big data communications framework : insights into big data mastery for information professionals -- Data scientists wanted : career opportunities in a big data world.
Record Nr. UNINA-9910817037103321
Affelt Amy L. <1970->  
Medford, New Jersey : , : Information Today, Inc., , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in data mining and modeling, Hong Kong, 27-28 June 2002 [[electronic resource] /] / editors, Wai-Ki Ching, Michael Kwok-Po Ng
Advances in data mining and modeling, Hong Kong, 27-28 June 2002 [[electronic resource] /] / editors, Wai-Ki Ching, Michael Kwok-Po Ng
Pubbl/distr/stampa Singapore ; ; River Edge, NJ, : World Scientific, 2003
Descrizione fisica 1 online resource (197 p.)
Disciplina 005.741
006.312
Altri autori (Persone) ChingWai Ki <1969->
NgMichael K
Soggetto topico Data mining
Database searching
Soggetto genere / forma Electronic books.
ISBN 1-281-37299-4
9786611372996
981-270-495-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto CONTENTS; Data Mining; Data Modeling; Preface; Author Index; Algorithms for Mining Frequent Sequences Ben Kao and Ming-Hua Zhang; High Dimensional Feature Selection for Discriminant Microarray Data Analysis Ju-Fu Feng, Jiang-Xin Shi and Qing-Yun Shi; Clustering and Cluster Validation in Data Mining Joshua Zhe-Xue Huang, Hong-Qiang Rong, Jessica Ting, Yun-Ming Ye and Qi-Ming Huang; Cluster Analysis Using Unidimensional Scaling Pui-Lam hung , Chi-Yin Li and Kin-Nam Lau; Automatic Stock Trend Prediction by Real Time News Gabriel Pui-Cheong Fung, Jeffrey Xu Yu and Wai Lam
From Associated Implication Networks to Intermarket Analysis Phil Chi- Wang Tse and Ji-Ming Liu Automating Technical Analysis Philip Leung-Ho Yu, Kin Lam and Sze-Hong Ng; A Divide-and-Conquer Fast Implementation of Radial Basis Function Networks with Application to Time Series Forecasting Rong-Bo Huang, Yiu-Ming Cheung and Lap-Tak Law; Learning Sunspot Series Dynamics by Recurrent Neural Networks Leong-Kwan Li; Independent Component Analysis: The One-Bit-Matching Conjecture and a Simplified LPM-ICA Algorithm Zhi-Yong Liu, Kai-Chun Chiu and Lei Xu
An Higher-Order Markov Chain Model for Prediction of Categorical Data Sequences Wai-Ki Ching, Eric Siu-Leung Fung and Michael Kwok-Po Ng An Application of the Mixture Autoregressive Model: A Case Study of Modelling Yearly Sunspot Data Kevin Kin-Foon Wong and Chun-Shan Wong; Bond Risk and Return in the SSE Long-Zhen Fan; Mining Loyal Customers: A Practical Use of the Repeat Buying Theory Hing-Po Lo, Xiao-Ling Lu and Zoe Sau-Chun Ng
Record Nr. UNINA-9910451311303321
Singapore ; ; River Edge, NJ, : World Scientific, 2003
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in data mining and modeling, Hong Kong, 27-28 June 2002 [[electronic resource] /] / editors, Wai-Ki Ching, Michael Kwok-Po Ng
Advances in data mining and modeling, Hong Kong, 27-28 June 2002 [[electronic resource] /] / editors, Wai-Ki Ching, Michael Kwok-Po Ng
Pubbl/distr/stampa Singapore ; ; River Edge, NJ, : World Scientific, 2003
Descrizione fisica 1 online resource (197 p.)
Disciplina 005.741
006.312
Altri autori (Persone) ChingWai Ki <1969->
NgMichael K
Soggetto topico Data mining
Database searching
ISBN 1-281-37299-4
9786611372996
981-270-495-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto CONTENTS; Data Mining; Data Modeling; Preface; Author Index; Algorithms for Mining Frequent Sequences Ben Kao and Ming-Hua Zhang; High Dimensional Feature Selection for Discriminant Microarray Data Analysis Ju-Fu Feng, Jiang-Xin Shi and Qing-Yun Shi; Clustering and Cluster Validation in Data Mining Joshua Zhe-Xue Huang, Hong-Qiang Rong, Jessica Ting, Yun-Ming Ye and Qi-Ming Huang; Cluster Analysis Using Unidimensional Scaling Pui-Lam hung , Chi-Yin Li and Kin-Nam Lau; Automatic Stock Trend Prediction by Real Time News Gabriel Pui-Cheong Fung, Jeffrey Xu Yu and Wai Lam
From Associated Implication Networks to Intermarket Analysis Phil Chi- Wang Tse and Ji-Ming Liu Automating Technical Analysis Philip Leung-Ho Yu, Kin Lam and Sze-Hong Ng; A Divide-and-Conquer Fast Implementation of Radial Basis Function Networks with Application to Time Series Forecasting Rong-Bo Huang, Yiu-Ming Cheung and Lap-Tak Law; Learning Sunspot Series Dynamics by Recurrent Neural Networks Leong-Kwan Li; Independent Component Analysis: The One-Bit-Matching Conjecture and a Simplified LPM-ICA Algorithm Zhi-Yong Liu, Kai-Chun Chiu and Lei Xu
An Higher-Order Markov Chain Model for Prediction of Categorical Data Sequences Wai-Ki Ching, Eric Siu-Leung Fung and Michael Kwok-Po Ng An Application of the Mixture Autoregressive Model: A Case Study of Modelling Yearly Sunspot Data Kevin Kin-Foon Wong and Chun-Shan Wong; Bond Risk and Return in the SSE Long-Zhen Fan; Mining Loyal Customers: A Practical Use of the Repeat Buying Theory Hing-Po Lo, Xiao-Ling Lu and Zoe Sau-Chun Ng
Record Nr. UNINA-9910783917603321
Singapore ; ; River Edge, NJ, : World Scientific, 2003
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in knowledge discovery and data mining : 11th Pacific-Asia conference, PAKDD 2007, Nanjing, China, May 22-25, 2007 ; proceedings / / Qiang Yang; Zhi-Hua Zhou; Hang Li
Advances in knowledge discovery and data mining : 11th Pacific-Asia conference, PAKDD 2007, Nanjing, China, May 22-25, 2007 ; proceedings / / Qiang Yang; Zhi-Hua Zhou; Hang Li
Edizione [1st ed. 2007.]
Pubbl/distr/stampa Berlin, Germany ; ; New York, New York : , : Springer, , [2007]
Descrizione fisica 1 online resource (1183 p.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Database searching
Data mining
Database management
ISBN 1-280-94403-X
9786610944033
3-540-71701-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Keynote Speeches -- Regular Papers -- Short Papers.
Record Nr. UNISA-996465629403316
Berlin, Germany ; ; New York, New York : , : Springer, , [2007]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in knowledge discovery and data mining : 6th Pacific-Asia conference, PAKDD 2002, Taipei, Taiwan, May 6-8, 2002 : proceedings / / Ming-Syan Chen; Philip S. Yu; Bing Liu
Advances in knowledge discovery and data mining : 6th Pacific-Asia conference, PAKDD 2002, Taipei, Taiwan, May 6-8, 2002 : proceedings / / Ming-Syan Chen; Philip S. Yu; Bing Liu
Edizione [1st ed. 2002.]
Pubbl/distr/stampa Berlin, Germany ; ; New York, New York : , : Springer, , [2002]
Descrizione fisica 1 online resource (XIV, 570 p.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Database searching
Data mining
Database management
ISBN 3-540-47887-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Industrial Papers (Invited) -- Network Data Mining and Analysis: The Project -- Privacy Preserving Data Mining: Challenges and Opportunities -- Survey Papers (Invited) -- A Case for Analytical Customer Relationship Management -- On Data Clustering Analysis: Scalability, Constraints, and Validation -- Association Rules (I) -- Discovering Numeric Association Rules via Evolutionary Algorithm -- Efficient Rule Retrieval and Postponed Restrict Operations for Association Rule Mining -- Association Rule Mining on Remotely Sensed Images Using P-trees -- On the Efficiency of Association-Rule Mining Algorithms -- Classification (I) -- A Function-Based Classifier Learning Scheme Using Genetic Programming -- SNNB: A Selective Neighborhood Based Naïve Bayes for Lazy Learning -- A Method to Boost Naïve Bayesian Classifiers -- Toward Bayesian Classifiers with Accurate Probabilities -- Interestingness -- Pruning Redundant Association Rules Using Maximum Entropy Principle -- A Confidence-Lift Support Specification for Interesting Associations Mining -- Concise Representation of Frequent Patterns Based on Generalized Disjunction-Free Generators -- Mining Interesting Association Rules: A Data Mining Language -- The Lorenz Dominance Order as a Measure of Interestingness in KDD -- Sequence Mining -- Efficient Algorithms for Incremental Update of Frequent Sequences -- DELISP: Efficient Discovery of Generalized Sequential Patterns by Delimited Pattern-Growth Technology -- Self-Similarity for Data Mining and Predictive Modeling A Case Study for Network Data -- A New Mechanism of Mining Network Behavior -- Clustering -- M-FastMap: A Modified FastMap Algorithm for Visual Cluster Validation in Data Mining -- An Incremental Hierarchical Data Clustering Algorithm Based on Gravity Theory -- Adding Personality to Information Clustering -- Clustering Large Categorical Data -- Web Mining -- WebFrame: In Pursuit of Computationally and Cognitively Efficient Web Mining -- Naviz:Website Navigational Behavior Visualizer -- Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs -- Automatic Information Extraction for Multiple Singular Web Pages -- Association Rules (II) -- An Improved Approach for the Discovery of Causal Models via MML -- SETM*-MaxK: An Efficient SET-Based Approach to Find the Largest Itemset -- Discovery of Ordinal Association Rules -- Value Added Association Rules -- Top Down FP-Growth for Association Rule Mining -- Semi-structure & Concept Mining -- Discovery of Frequent Tag Tree Patterns in Semistructured Web Documents -- Extracting Characteristic Structures among Words in Semistructured Documents -- An Efficient Algorithm for Incremental Update of Concept Spaces -- Data Warehouse and Data Cube -- Efficient Constraint-Based Exploratory Mining on Large Data Cubes -- Efficient Utilization of Materialized Views in a Data Warehouse -- Bio-Data Mining -- Mining Interesting Rules in Meningitis Data by Cooperatively Using GDT-RS and RSBR -- Evaluation of Techniques for Classifying Biological Sequences -- Efficiently Mining Gene Expression Data via Integrated Clustering and Validation Techniques -- Classification (II) -- Adaptive Generalized Estimation Equation with Bayes Classifier for the Job Assignment Problem -- GEC: An Evolutionary Approach for Evolving Classifiers -- An Efficient Single-Scan Algorithm for Mining Essential Jumping Emerging Patterns for Classification -- A Method to Boost Support Vector Machines -- Temporal Mining -- Distribution Discovery: Local Analysis of Temporal Rules -- News Sensitive Stock Trend Prediction -- User Profiling for Intrusion Detection Using Dynamic and Static Behavioral Models -- Classification (III) -- Incremental Extraction of Keyterms for Classifying Multilingual Documents in the Web -- k-nearest Neighbor Classification on Spatial Data Streams Using P-trees -- Interactive Construction of Classification Rules -- Outliers, Missing Data, and Causation -- Enhancing Effectiveness of Outlier Detections for Low Density Patterns -- Cluster-Based Algorithms for Dealing with Missing Values -- Extracting Causation Knowledge from Natural Language Texts -- Mining Relationship Graphs for Effective Business Objectives.
Record Nr. UNISA-996465985203316
Berlin, Germany ; ; New York, New York : , : Springer, , [2002]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in knowledge discovery and data mining : 6th Pacific-Asia conference, PAKDD 2002, Taipei, Taiwan, May 6-8, 2002 : proceedings / / Ming-Syan Chen; Philip S. Yu; Bing Liu
Advances in knowledge discovery and data mining : 6th Pacific-Asia conference, PAKDD 2002, Taipei, Taiwan, May 6-8, 2002 : proceedings / / Ming-Syan Chen; Philip S. Yu; Bing Liu
Edizione [1st ed. 2002.]
Pubbl/distr/stampa Berlin, Germany ; ; New York, New York : , : Springer, , [2002]
Descrizione fisica 1 online resource (XIV, 570 p.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Database searching
Data mining
Database management
ISBN 3-540-47887-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Industrial Papers (Invited) -- Network Data Mining and Analysis: The Project -- Privacy Preserving Data Mining: Challenges and Opportunities -- Survey Papers (Invited) -- A Case for Analytical Customer Relationship Management -- On Data Clustering Analysis: Scalability, Constraints, and Validation -- Association Rules (I) -- Discovering Numeric Association Rules via Evolutionary Algorithm -- Efficient Rule Retrieval and Postponed Restrict Operations for Association Rule Mining -- Association Rule Mining on Remotely Sensed Images Using P-trees -- On the Efficiency of Association-Rule Mining Algorithms -- Classification (I) -- A Function-Based Classifier Learning Scheme Using Genetic Programming -- SNNB: A Selective Neighborhood Based Naïve Bayes for Lazy Learning -- A Method to Boost Naïve Bayesian Classifiers -- Toward Bayesian Classifiers with Accurate Probabilities -- Interestingness -- Pruning Redundant Association Rules Using Maximum Entropy Principle -- A Confidence-Lift Support Specification for Interesting Associations Mining -- Concise Representation of Frequent Patterns Based on Generalized Disjunction-Free Generators -- Mining Interesting Association Rules: A Data Mining Language -- The Lorenz Dominance Order as a Measure of Interestingness in KDD -- Sequence Mining -- Efficient Algorithms for Incremental Update of Frequent Sequences -- DELISP: Efficient Discovery of Generalized Sequential Patterns by Delimited Pattern-Growth Technology -- Self-Similarity for Data Mining and Predictive Modeling A Case Study for Network Data -- A New Mechanism of Mining Network Behavior -- Clustering -- M-FastMap: A Modified FastMap Algorithm for Visual Cluster Validation in Data Mining -- An Incremental Hierarchical Data Clustering Algorithm Based on Gravity Theory -- Adding Personality to Information Clustering -- Clustering Large Categorical Data -- Web Mining -- WebFrame: In Pursuit of Computationally and Cognitively Efficient Web Mining -- Naviz:Website Navigational Behavior Visualizer -- Optimal Algorithms for Finding User Access Sessions from Very Large Web Logs -- Automatic Information Extraction for Multiple Singular Web Pages -- Association Rules (II) -- An Improved Approach for the Discovery of Causal Models via MML -- SETM*-MaxK: An Efficient SET-Based Approach to Find the Largest Itemset -- Discovery of Ordinal Association Rules -- Value Added Association Rules -- Top Down FP-Growth for Association Rule Mining -- Semi-structure & Concept Mining -- Discovery of Frequent Tag Tree Patterns in Semistructured Web Documents -- Extracting Characteristic Structures among Words in Semistructured Documents -- An Efficient Algorithm for Incremental Update of Concept Spaces -- Data Warehouse and Data Cube -- Efficient Constraint-Based Exploratory Mining on Large Data Cubes -- Efficient Utilization of Materialized Views in a Data Warehouse -- Bio-Data Mining -- Mining Interesting Rules in Meningitis Data by Cooperatively Using GDT-RS and RSBR -- Evaluation of Techniques for Classifying Biological Sequences -- Efficiently Mining Gene Expression Data via Integrated Clustering and Validation Techniques -- Classification (II) -- Adaptive Generalized Estimation Equation with Bayes Classifier for the Job Assignment Problem -- GEC: An Evolutionary Approach for Evolving Classifiers -- An Efficient Single-Scan Algorithm for Mining Essential Jumping Emerging Patterns for Classification -- A Method to Boost Support Vector Machines -- Temporal Mining -- Distribution Discovery: Local Analysis of Temporal Rules -- News Sensitive Stock Trend Prediction -- User Profiling for Intrusion Detection Using Dynamic and Static Behavioral Models -- Classification (III) -- Incremental Extraction of Keyterms for Classifying Multilingual Documents in the Web -- k-nearest Neighbor Classification on Spatial Data Streams Using P-trees -- Interactive Construction of Classification Rules -- Outliers, Missing Data, and Causation -- Enhancing Effectiveness of Outlier Detections for Low Density Patterns -- Cluster-Based Algorithms for Dealing with Missing Values -- Extracting Causation Knowledge from Natural Language Texts -- Mining Relationship Graphs for Effective Business Objectives.
Record Nr. UNINA-9910143906403321
Berlin, Germany ; ; New York, New York : , : Springer, , [2002]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bio-inspired computing for information retrieval applications / / D. P. Acharjya and Anirban Mitra
Bio-inspired computing for information retrieval applications / / D. P. Acharjya and Anirban Mitra
Autore Acharjya D. P.
Pubbl/distr/stampa Hershey, Pennsylvania : , : IGI Global, , 2017
Descrizione fisica 1 online resource (411 pages)
Disciplina 005.74
Collana Advances in Knowledge Acquisition, Transfer, and Management (AKATM) Book Series
Soggetto topico Natural computation
Information storage and retrieval systems
Querying (Computer science)
Database searching
Soggetto genere / forma Electronic books.
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910164874403321
Acharjya D. P.  
Hershey, Pennsylvania : , : IGI Global, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Clojure data analysis cookbook / / Eric Rochester
Clojure data analysis cookbook / / Eric Rochester
Autore Rochester Eric
Edizione [1st edition]
Pubbl/distr/stampa Birmingham, UK, : Packt Pub., c2013
Descrizione fisica 1 online resource (342 p.)
Disciplina 005.133
Soggetto topico Database searching
Clojure (Computer program language)
ISBN 1-68015-416-8
1-299-44085-1
1-78216-265-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Importing Data for Analysis; Introduction; Creating a new project; Reading CSV data into Incanter datasets; Reading JSON data into Incanter datasets; Reading data from Excel with Incanter; Reading data from JDBC databases; Reading XML data into Incanter datasets; Scraping data from tables in web pages; Scraping textual data from web pages; Reading RDF data; Reading RDF data with SPARQL; Aggregating data from different formats; Chapter 2: Cleaning and Validating Data
IntroductionCleaning data with regular expressions; Maintaining consistency with synonym maps; Identifying and removing duplicate data; Normalizing numbers; Rescaling values; Normalizing dates and times; Lazily processing very large data sets; Sampling from very large data sets; Fixing spelling errors; Parsing custom data formats; Validating data with Valip; Chapter 3: Managing Complexity with Concurrent Programming; Introduction; Managing program complexity with STM; Managing program complexity with agents; Getting better performance with commute; Combining agents and STM
Maintaining consistency with ensureIntroducing safe side effects into the STM; Maintaining data consistency with validators; Tracking processing with watchers; Debugging concurrent programs with watchers; Recovering from errors in agents; Managing input with sized queues; Chapter 4: Improving Performance with Parallel Programming; Introduction; Parallelizing processing with pmap; Parallelizing processing with Incanter; Partitioning Monte Carlo simulations for better pmap performance; Finding the optimal partition size with simulated annealing; Parallelizing with reducers
Generating online summary statistics with reducersHarnessing your GPU with OpenCL and Calx; Using type hints; Benchmarking with Criterium; Chapter 5: Distributed Data Processing with Cascalog; Introduction; Distributed processing with Cascalog and Hadoop; Querying data with Cascalog; Distributing data with Apache HDFS; Parsing CSV files with Cascalog; Complex queries with Cascalog; Aggregating data with Cascalog; Defining new Cascalog operators; Composing Cascalog queries; Handling errors in Cascalog workflows; Transforming data with Cascalog
Executing Cascalog queries in the Cloud with PalletChapter 6: Working with Incanter Datasets; Introduction; Loading Incanter's sample datasets; Loading Clojure data structures into datasets; Viewing datasets interactively with view; Converting datasets to matrices; Using infix formulas in Incanter; Selecting columns with ; Selecting rows with ; Filtering datasets with where; Grouping data with group-by; Saving datasets to CSV and JSON; Projecting from multiple datasets with join; Chapter 7: Preparing for and Performing Statistical Data Analysis with Incanter; Introduction
Generating summary statistics with rollup
Record Nr. UNINA-9911006788503321
Rochester Eric  
Birmingham, UK, : Packt Pub., c2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui