Data Science For Dummies, 2nd Edition 2nd Edition

Broad scope and current. This is the book for anyone looking to see the range of available tools (from machine learning to d3.js) for data science. She is better than most authors at the intro stage of every topic -- for example, why do I care about reducing dimensionality? How to predict groupings within a dataset? One reviewer said that this book does not get much into implementation of the concepts. That is true, but then how could you in less than 400 pages? Entire books are written on just one topic, such as time series prediction models. The key for beginners and intermediate data science practitioners is to fully understand options before spending weeks or months going down a rabbit hole (wrong model). I can say this with some regret because I wasted a lot of my own time in a steel demand prediction project a few years back. Had I been better acquainted with options, I probably would have completed it in half the time. Unless you are already a guru, this book is well worth the money.

If you’re curious what data science is and isn’t, this book is perfect. It gives information in a little bit of everything. It also has a LOT of great references to come back to if you need data sets or specific program needs. This book is more of an overview which I’d highly recommend if you’re just beginning your data science journey. It isn’t a walkthrough of the in depth programming. It’s more of a intro to data science class which is still very involved.

This book is a geat start for anyone who is curious to know about data, In today's world every aspect of the business and its future relies on the historical data and this is a great book which covers-1. Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value2. Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL3. Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things4. Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate

I am a complete novice when it comes to data science. Most of the material left me more or less confused. The worst part of the book was the author's discussion on Python. As someone who is a Python expert she didn't do justice to her chapter on that subject as far as I am concerned. Lots of definitions and then the snippets of coding examples were too confusing. What would have worked better is to give a introduction to Python and then work through simple examples that were fully annotated.

Nicely made. Easy to follow

Sorts out the high level topics and allows understanding to decide if you want to jump into this field.Package was open on one end when delivered; contents could have easily fallen out. Looks like the end of the padded envelope was intentionally torn open and someone decided the 'nerd' books were a disappointment . . .

Good source of basic knoweldge.

I like the way the author explains complex concepts in simple words, using relevant examples.