Fai clic su di un'immagine per andare a Google Ricerca Libri.
Sto caricando le informazioni... Developing Analytic Talent Becoming a Data Scientist (edizione 2014)di (Ph. D.) Vincent Granville
Informazioni sull'operaDeveloping Analytic Talent: Becoming a Data Scientist di Vincent Granville
Nessuno Sto caricando le informazioni...
Iscriviti per consentire a LibraryThing di scoprire se ti piacerà questo libro. Attualmente non vi sono conversazioni su questo libro. There are some good nuggets of information here and in many cases way too much information. But then maybe that is the hazard of being a data scientist/author--you want to give everybody ALL the information so that they can then dig out the nuggets themselves. Unfortunately that does not make a good technical book. IMPO (in my professional opinion as a former editor for technical books) a good technical book is an author taking the reader by the hand and telling them what they need to know--not spewing gads of links, bulleted lists and drifting off topic in the middle of the chapter to explore a math problem. I could blame the editor or maybe this was just a cowboy author. Obviously the author is brilliant--but that doesn't make this a good or easy book to read. ( ) [Leaving aside the, by now, well-known, pay for Amazon reviews episode.] This is a mess of a book. Based on other reviews, I see I'm not the only one who found it confusing and certainly not a good illustration of the title. A big chunk of the book is dedicated to defining data science as opposed to what the author calls "fake data science". That is done in a tone that goes from condescending to resentful (with the usual critique that [insert your favorite emerging field] is not properly taught in university, that's par for the course). Then, the author abruptly goes into illustrations that people with no background in statistics (but not the old, bad, statistics, the new cool one developed by the author) will have a hard time following (so, so much for the "developing" part in the title). And the book ends with some job market data (interview questions, salary survey, etc.). In the end, the author does not give a lot of info on how to start in data science. The entire book, and especially the case chapters, assume extensive knowledge of the field. Readers will find bits and pieces of useful information here and there, but it feels like needles in a hay stack. nessuna recensione | aggiungi una recensione
Learn the skills needed for the most in-demand tech job Harvard Business Review calls it the sexiest tech job of the 21st century. Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT professionals. Data science involves extracting, creating, and processing data to turn it into business value. This guide discusses the essential skills, such as statistics and visualization techniques, and covers everything from analytical recipes and data science tricks to common j Non sono state trovate descrizioni di biblioteche |
Discussioni correntiNessunoCopertine popolari
Google Books — Sto caricando le informazioni... GeneriSistema Decimale Melvil (DDC)020Information Library and Information Sciences Library ScienceClassificazione LCVotoMedia:
Sei tu?Diventa un autore di LibraryThing. |