• Data Science: The Ultimate Guide to Data Analytics, Data Mining, Data Warehousing, Data Visualization, Regression Analysis, Database Querying, Big Data for Business and Machine Learning for Beginners

  • By: Herbert Jones
  • Narrated by: Sam Slydell
  • Length: 5 hrs and 18 mins
  • Unabridged Audiobook
  • 4.2 out of 5 stars (75 ratings)
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Publisher's Summary

Do you want to expand your skills from being a basic data scientist to becoming an expert data scientist ready to solve real-world data-centric issues? Exploring this audiobook could be a step in the right direction.

Discover two comprehensive manuscripts in one audiobook:

  • Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't
  • Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database Querying, and Machine Learning for Beginners

Part one of this audiobook will cover topics such as:

  • What data science is
  • What it takes to become an expert in data science
  • Best data mining techniques to apply in data
  • Data visualization
  • Logistic regression
  • Data engineering
  • Machine learning
  • Big data analytics
  • And much more!

Part two of this audiobook will discuss the following topics:

  • How big data works and why it is so important
  • How to do an explorative data analysis
  • Working with data mining
  • How to mine text to get the data
  • Some amazing machine learning algorithms to help with data science
  • How to do data modeling
  • Data visualization
  • How to use data science to help your business grow
  • Tips to help you get started with data science
  • And much, much more!

So listen to this audiobook now if you want to learn more about data science!

©2018 Herbert Jones (P)2018 Herbert Jones

What listeners say about Data Science: The Ultimate Guide to Data Analytics, Data Mining, Data Warehousing, Data Visualization, Regression Analysis, Database Querying, Big Data for Business and Machine Learning for Beginners

Average Customer Ratings
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There is no negative or zero stars. Bad

this is the worst audio book I have ever acquired from audible. it is a compendium of stock phrases taken from some random Web sites,

2 people found this helpful

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Skip it

This book is too deep for the complete novice and does not have any depth for the armchair data scientist. Though I did not like the book, I went back to listen and try to think who I thought the correct audience is. I don’t think there is one.

4 people found this helpful

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Excellent starter course

This wasn't exactly what I was thinking it was, but it turned out to be something that I feel I needed. Happy that I bought it anyway.

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Recommended reading for newbies

The book is an introduction into machine learning techniques that covers many of the topics like; Data Analytics, Data Mining, Data Warehousing, Data Visualization, Regression Analysis, Database Querying, Big Data for Business without going into many detailed explanations.

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Good entry level book for high level concepts

I will need a second pass on the book, but I think it gave a great introduction to the world of machine learning including; Data Analytics, Data Mining, Data Warehousing, Data Visualization, Regression Analysis, Database Querying, Big Data for Business.

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Learn ML with ease here.

I want to tell everybody; this book is really great for who really wants to jump in the ML field. Lots of real-world outlines; a perfect example is one of the best features of the book.

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Great introduction at the right time.

New to Data Science but have done programming in previous jobs. I found this book extremely helpful. It gives a great introduction to Data Analytics, Data Mining, Data Warehousing, Data Visualization, Regression Analysis, Database Querying, Big Data for Business, and Machine Learning for Beginners while urging your curiosity to explore and learn more. Love it.

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The Ultimate Guide to Data Analytics

This is the first Machine Learning book I’ve got. The author knows his stuff but doesn’t mind slowing down and explaining what it all means in a well thought out way.

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The right level for me

I want to say that this book is perfect if you exclude the exercises well. In my opinion, It's balanced with audio and provides a high-level overview of concepts, models, etc.

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A straightforward book.

You will not waste your time with understanding the fundamental mathematics and instead leverages the use of publicly available Python libraries. The math of Machine Learning can easily be intimidating, and I commend the authors from shying away from it.

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  • Amazon Customer
  • 01-07-19

muddled

I felt like this was all over the place both in terms of content and level of detail / granularity for the sections. Some sections were really detailed while others were extremely sparse and some sounded like they had just been lifted off a Google search and weren't really tied in.

4 people found this helpful

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  • Anonymous User
  • 07-21-21

The format of the book fails.

Data science is a highly visual discipline that seems in stark contrast to the very essence of the audiobook format. Indeed this audiobook is quite useless without a hard copy at hand, sadly.

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    4 out of 5 stars
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  • Hilda Bird
  • 10-17-19

Its Good

This book is for people to gain an understanding of what data science truly is and how it can help with business decisions. The authors do a great job of keeping the concepts applicable to actual business events.

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    4 out of 5 stars
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  • S. William
  • 10-16-19

Handy Guide

This book really helps me understand major data science concepts as I work in tech and constantly interface with a technical data science product + data business contacts.

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    4 out of 5 stars
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  • Kirk Smith
  • 10-16-19

Excellent

This book is an excellent introduction to data science for shaping how one would think about information. I went over many different methodologies and explained in such a way that was concise and relatively easy to follow.

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    4 out of 5 stars
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  • Candy Carpenter
  • 10-14-19

Essential

This book is ideal for anyone looking to understand data science, and especially those who might interact with data scientists at work. Roughly half the book deals with the essential data mining algorithms. The focus is on understanding what the algorithms do, not the details of how they do it, so implementation details are omitted.

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    4 out of 5 stars
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  • Zack Livingston
  • 10-13-19

I Liked It

This book will not make you an expert but at least you will know what the experts are talking about. It is written with just enough math for the non-PhD manager to understand.

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    4 out of 5 stars
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  • Rhonda Strong
  • 10-12-19

Data Science

An excellent discussion of data science methods without an excessive focus on mathematical elements. These are included at a level that can be understood for the skilled marketer who has a background but does not wish to go deep into the math. I recommend it.

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    1 out of 5 stars
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  • DaveOnFlickr
  • 09-23-19

This is more like an audible Wikipedia page

I actually think this was written by a machine. It’s just a collection of lists, brands, etc and very brief expansion on some of them. It’s so dull and has added nothing to my understanding of the material.

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  • G. Reading
  • 06-26-19

all over the place

Awful. A narrator who sent me to sleep, content which is not cohesive or even helpful. It flips from talking about univariate linear regression (I think, if we're over the age of 10, we know what this is) to how to cross validate over the course of two consecutive sentences. Full of empty platitudes. Listens more like a college students' flow-of-thought diary than a pro audiobook. Maybe it's better in book form but audio does not suit this book.

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    3 out of 5 stars
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  • Anonymous User
  • 07-18-20

Not really teaching you anything

It only gives you a list of names without much explanations or examples. I felt like I've only learned a few jargons.

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  • Galahadoc
  • 04-28-19

Mostly high level

This book is mostly high level but sometimes gets super detailed, which makes it a bit hard to read. There are some parts that are repeated. Would be good if some of the recommended sites and resources would be made available with a link or pdf. Otherwise, worth the read if you want some high level views. Performance really good.