Gratuit avec l'essai de 30 jours

  • Data Science for Business

  • Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database Querying, and Machine Learning for Beginners
  • Auteur(s): Herbert Jones
  • Narrateur(s): Sam Slydell
  • Durée: 3 h et 1 min
  • 5,0 out of 5 stars (1 évaluation)

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Description

Do you want to learn about data science but aren't in the mood to read a boring textbook? This data science audiobook could be the answer for which you're looking....

Data science has a huge impact on how companies conduct business, and those who don't learn about this revolutionary field could be left behind. 

You see, data science will help you make better decisions, know what products and services to release, and how to provide better service to your customers. It is all done by collecting and sorting through a large amount of information so you have the right sources behind you when you make a major decision. 

In this guidebook, you will discover more about data science and how to get started in this field.

This audiobook will discuss the following topics:

  • What is data science?
  • 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 if you are ready to get started with data science, listen to this audiobook now!

©2018 Herbert Jones (P)2018 Herbert Jones

Ce que les auditeurs disent de Data Science for Business

Moyenne des évaluations de clients
Au global
  • 5 out of 5 stars
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  • Au global
    1 out of 5 stars
  • Performance
    3 out of 5 stars
  • Histoire
    1 out of 5 stars
  • Jack Regehr
  • 2021-11-27

Useless

This book is useless; don’t waste your time. It gives the most basic explanation of the terms then gives random facts about some algorithms.

  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    4 out of 5 stars
  • Dean Gladish
  • 2020-04-10

a very helpful summary of the fundamental models.

this audiobook is truly quite brief and also excellent. rest assured this gives you a perfect summary.

  • Au global
    1 out of 5 stars
  • Performance
    3 out of 5 stars
  • Histoire
    2 out of 5 stars
  • TickTock
  • 2019-03-27

Convexing

This book was either way too high level in some chapters and in others very in-depth. To make this book usable to the reader, it should include a pdf copy of it or a powerpoint of the topics discussed. Reading a ML formula to me isn't going to help me in anyway.

  • Au global
    4 out of 5 stars
  • Performance
    4 out of 5 stars
  • Histoire
    4 out of 5 stars
  • Alexander B. Talbot
  • 2018-10-26

Very cursory audible.

Does not even try to go in depth because the book is very cursory so you would need a great attention to understand the stuff.

  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    5 out of 5 stars
  • Gail Bishop
  • 2018-10-26

Unpretentious, clear, and highly informative.

I can understand why this audible is going so popular. This book is mostly machine learning under Data Science - no data engineering, munging, code (or math) here.

  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    5 out of 5 stars
  • Alberta Augustine
  • 2018-10-26

Great and quick intro

It’s a great quick introduction to the most common Data Science for Business methods and the intuitions behind them. While not very detailed, it does a good job for what it sets out to do.

  • Au global
    5 out of 5 stars
  • Performance
    5 out of 5 stars
  • Histoire
    5 out of 5 stars
  • David Sherrer
  • 2018-10-26

Great summary (3 hrs and 1 min)

This is a tremendous resource for anyone looking for a refresher or a basic introduction to machine learning from Data Science. The examples were easy to understand and the lessons are heavy on theory.