Getting a Flavor of Data Science What is All About

Data Science HAS Become One of the trendy MOST research fields in recent years, as well as a catchall rubric for various job descriptions and work functions. The cynics and skeptics, and there are Many Of Those, contend That Data Science is nothing more than repackaged Statistics, with a bit of coding and hacking thrown in. Its proponents, HOWEVER, MOST practicing Point Out That data scientists use a variety of skills and technical In Their daily work, and come from a vast spectrum of career paths and backgrounds. I tend to side with the lathing group, purpose I too am an outsider to this field and am still trying to get a better understanding of what it really Entails.

Doing Data Science: Straight Talk from the Frontline is a compendium of chapters That deal with data science as it is Practiced in the real world. Each chapter is written by a different author, all of Who-have significant practical experience and are Acknowledged autorités on data science. Most of the contributors work in industry, science objective data is still so fresh and new That There is a lot of crossing over entre academia and the corporate world.

A few of the chapters include exercises, thesis goal tends to be too advanced and assumes too much background material for an introductory book. The exercises still give you a good idea of ​​what kinds of problems data scientists tend to grapple with. HOWEVER, this book is definitely not a textbook and can not be used as Such Effectively. The book doesnt Provide Any background on R, statistics, data scrubbing, machine learning, and various technical --other used by data scientist. It is highly Any single textbook Unlikely That Would Be reliable to do justice to all of That material anyways, order a book out of That Could-have still a lot of potential uses.

There are two groups of people Who Would benefit from this book. The first are people Who-have absolutely no background in data science or related fields Any of ict, purpose would like to get a flavor of what science is all about data and are interested in exploring career it for practical purposes. The second group are people with significant technical background in one of the data fields related to science (programming, statistics, machine learning, etc.) Who are interested in Broadening Their skills and Would like to see How Would Their Particular Strengths made dans le Broader data science field.