Data Science And Bigdata

Data Science and Analytics Career Paths and Certifications  eBooks & eLearning

Posted by naag at Aug. 15, 2016
Data Science and Analytics Career Paths and Certifications

Data Science and Analytics Career Paths and Certifications
MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 1 Hours | 132 MB
Genre: eLearning | Language: English
A collection of Advanced Data Science and Machine Learning Interview Questions Solved in Python and Spark (II)

Dr Antonio Gulli , "A collection of Advanced Data Science and Machine Learning Interview Questions Solved in Python and Spark (II): Hands-on Big Data and Machine … of Programming Interview Questions"
2015 | ISBN-10: 1518678645 | 106 pages | Djvu | 1 MB

Data Science and Big Data Computing  eBooks & eLearning

Posted by Underaglassmoon at July 8, 2016
Data Science and Big Data Computing

Data Science and Big Data Computing: Frameworks and Methodologies
Springer | Software Engineering | August 6, 2016 | ISBN-10: 3319318594 | 332 pages | pdf | 5.34 mb

Editors: Mahmood, Zaigham (Ed.)
Reviews the latest research and practice in data science and big data
Discusses tools and techniques for big data storage and analytics
Describes the frameworks relevant to data science, and their application
SQL for Marketers: Dominate data analytics, data science, and big data (Data Science and Machine Learning in Python)

SQL for Marketers: Dominate data analytics, data science, and big data (Data Science and Machine Learning in Python) by LazyProgrammer
English | March 17, 2016 | ASIN: B01D42UBP4 | 45 Pages | AZW3/MOBI/EPUB/PDF (conv) | 1.77 MB

More and more companies these days are learning that they need to make DATA-DRIVEN decisions.
Data Science and Machine Learning with Python - Hands On

Data Science and Machine Learning with Python - Hands On
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 9 Hours | 2.50 GB
Genre: eLearning | Language: English

Become a data scientist in the tech industry! Comprehensive data mining and machine learning course with Python & Spark.
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by EMC Education Services
2015 | ISBN: 111887613X | English | 432 pages | True PDF | 40 MB
Analytics in a Big Data World: The Essential Guide to Data Science and its Applications

Bart Baesens, "Analytics in a Big Data World: The Essential Guide to Data Science and its Applications"
English | ISBN: 1118892704 | 2014 | 256 pages | PDF | 4 MB
Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by EMC Education Services
English | Jan 27, 2015 | ISBN: 111887613X | 432 Pages | EPUB/MOBI/AZW3/PDF (Converted) | 33 MB

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use.

Data Science and Classification by Hans-Hermann Bock [Repost]  

Posted by tanas.olesya at Dec. 1, 2014
Data Science and Classification by Hans-Hermann Bock [Repost]

Data Science and Classification (Studies in Classification, Data Analysis, and Knowledge Organization) by Hans-Hermann Bock
English | July 5, 2006 | ISBN: 3540344152 | 349 pages | PDF | 3 MB

Data Science and Classification provides new methodological developments in data analysis and classification. The broad and comprehensive coverage includes the measurement of similarity and dissimilarity, methods for classification and clustering, network and graph analyses, analysis of symbolic data, and web mining.

Data Science and Classification  

Posted by cruze at Oct. 13, 2007
284600
Batagelj, Bock, Ferligoj, Ziberna, "Data Science and Classification"
Springer | ISBN: 3540344152 | July 28, 2006 | 358 pages | PDF | 3.6 MB

This volume provides new methodological developments in data analysis and classification. A wide range of topics is covered that includes the measurement of similarity and dissimilarity, methods for classification and clustering, network and graph analyses, analysis of symbolic data, and web mining. Apart from structural and theoretical results the book shows how to apply the proposed to a variety of problems, for example in medicine, microarray analysis, social network structures, and music. The combination of new methodological advances with the wide range of real applications collected in this volume is of special value for researchers when choosing the appropriate among newly developed analytical tools for their research problems in classification and data analysis.