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Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

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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. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples 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. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!


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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. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples 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. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

55 review for Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data

  1. 4 out of 5

    Matt

    A good, broad textbook on data analysis and presentation in R, with introductory modelling techniques including regression, classification, clustering, association rule mining, and time series methods. Together with An Introduction to Statistical Learning with Applications in R by James et al., I'd recommend it to anyone aspiring to do quantitative research, be it data science, business/finance/economics, etc. A good, broad textbook on data analysis and presentation in R, with introductory modelling techniques including regression, classification, clustering, association rule mining, and time series methods. Together with An Introduction to Statistical Learning with Applications in R by James et al., I'd recommend it to anyone aspiring to do quantitative research, be it data science, business/finance/economics, etc.

  2. 4 out of 5

    David

    Great overview and enough detail of analytics models. Just the book I was looking for to go little deeper on understanding the analytical models (for non-data scientist)

  3. 4 out of 5

    Chris Finn

  4. 4 out of 5

    مشاعل

  5. 4 out of 5

    Louis

  6. 5 out of 5

    Jill Heinbigner

  7. 5 out of 5

    Suganya

  8. 5 out of 5

    Philip

  9. 5 out of 5

    John McKeever

  10. 4 out of 5

    Cyrille Savelief

  11. 5 out of 5

    Roel Castelein

  12. 4 out of 5

    Diego

  13. 5 out of 5

    Merin

  14. 4 out of 5

    Meher Ravali

  15. 5 out of 5

    Naveen

  16. 5 out of 5

    Wojtek Ptak

  17. 4 out of 5

    John

  18. 4 out of 5

    Srinivas

  19. 4 out of 5

    Nazmul Ahmed Noyon

  20. 4 out of 5

    Lyner Lim

  21. 4 out of 5

    Shathahir

  22. 4 out of 5

    Leonkap

  23. 5 out of 5

    Diego Montoliu

  24. 5 out of 5

    ساره خالد

  25. 4 out of 5

    Aparna

  26. 5 out of 5

    Dan Amrine

  27. 4 out of 5

    Ryan Wood

  28. 5 out of 5

    AlphaScale

  29. 5 out of 5

    Rajiv Kumar

  30. 5 out of 5

    John

  31. 5 out of 5

    Fg

  32. 4 out of 5

    Raul Zavala

  33. 4 out of 5

    Billy

  34. 4 out of 5

    Bhavuk

  35. 4 out of 5

    Milena Georgieva

  36. 5 out of 5

    Renilton

  37. 5 out of 5

    Sandeep

  38. 5 out of 5

    Rhian Thomas

  39. 5 out of 5

    Daniel

  40. 4 out of 5

    Jaron Clark

  41. 5 out of 5

    Fernando

  42. 4 out of 5

    Abbas

  43. 4 out of 5

    Abdallah Zayed

  44. 5 out of 5

    María Gertrudis

  45. 5 out of 5

    Rafael Morales

  46. 5 out of 5

    Yang Zhang

  47. 5 out of 5

    Chris

  48. 5 out of 5

    Sandeep Singh

  49. 4 out of 5

    Mw

  50. 4 out of 5

    Tiago Henriques

  51. 5 out of 5

    Loice

  52. 5 out of 5

    Tunji Akinbami

  53. 5 out of 5

    Stefan

  54. 5 out of 5

    Aamir.khan

  55. 5 out of 5

    Manvendra Lodha

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