!!> Ebook ➮ Practical Data Science with R ➯ Author Nina Zumel – Soaringeaglecasino.us

Practical Data Science with R Simply Put, Data Science Is The Discipline Of Extracting Meaning From Data While It Can Involve Deep Knowledge Of Statistics, Mathematics, Machine Learning, And Computer Science, For Most Non Academics, Data Science Looks Like Applying Analysis Techniques To Answer Key Business Questions Practical Data Science With R Lives Up To Its Name It Explains Basic Principles Without The Theoretical Mumbo Jumbo And Jumps Right To The Real Use Cases Faced While Collecting, Curating, And Analyzing The Data Crucial To The Success Of Businesses Readers Will Apply The R Programming Language And Statistical Analysis Techniques To Carefully Explained Examples Based In Marketing, Business Intelligence, And Decision Support, While Learning How To Create Instrumentation, Design Experiments Such As A B Tests, And Accurately Present Data To Audiences Of All Levels.Purchase Of The Print Book Includes A Free EBook In PDF, Kindle, And EPub Formats From Manning Publications.

!!> Ebook ➮ Practical Data Science with R  ➯ Author Nina Zumel – Soaringeaglecasino.us
  • Paperback
  • 450 pages
  • Practical Data Science with R
  • Nina Zumel
  • English
  • 23 January 2018
  • 9781617291562

    10 thoughts on “!!> Ebook ➮ Practical Data Science with R ➯ Author Nina Zumel – Soaringeaglecasino.us

  1. says:

    Practical data science with R is an original book, yet not a great one, and I would not recommend it This book belongs to the trend of data science by practitioners They promote themselves as material with a practical focus and accessible writing style However, usually they fail at explaining the theory behind This book suffers this malaise, it struggles to explain the principles and sometimes is even wrong about basic concepts in stats for e...

  2. says:

    Quickly scanned through this book The code base is well prepared The business use case are described Also glad to find that the author took care of model preparation, which is rare for a book on data science and R Drawbacks are obvious as well the theories behi...

  3. says:

    This is my January book for my read one work book per month New Year s resolution Good practical book on applying machine learning Lots of examples, though I probably would have appreciated effort to use a single domain or business , rather than constantly leaping around, just because taking a number of approaches to a single problem area is a useful skill to develop I d also have liked to see generic functions most of their illustrations would need to adapted For example, they used a notation in their function for calculation of Euclidean distance to indicate that you do the calculation for each dimension, but it would have been trivial to write the function to take the number of dimensions from the input vectors Final quibble is that their treatment of kernels and SVMs seemed far theoretical than the other sections.So not, a definitive reference, but definitely a good book to have on your shelf when working an ML project in R.Also, I seem to r...

  4. says:

    I m not always happy with the Manning texts in comparison to the ORly books but this one was great.Step by step instructions walk the reader through getting the results shown in the book.The code is all in a github repo, and the authors introduce new tools that they created SQL Screwdriver, et al for use by everyone This isn t a book about R per se, but a book about how to choose and attack datascience projects and maybe the title is misleading since most of us data science types actually do data analysis or data engineering The chapter on classification and clustering algorithms is a perfect example They use R to teach the a...

  5. says:

    This book is great introduction to Data Science in R However, as the title implies, it is geared towards those looking for only a high level, quick overview to Data Science practices as they apply in the business world as well as how to communicate results to non practitioners and business partners If this is what you are looking for then I recommend this book If you are looking for a in depth introduction to the theory of data science and machine learning, I would look elsewhere, as the topics are covered in a very superficial manner Had I done research into this book before purchasing, I would not have bought it instead opting for a theoretical ...

  6. says:

    Location ND6 IRCAccession no DL026996

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