• Complain

Taieb - Data analysis with Python : a modern approach

Here you can read online Taieb - Data analysis with Python : a modern approach full text of the book (entire story) in english for free. Download pdf and epub, get meaning, cover and reviews about this ebook. year: 2018, publisher: Packt Publishing, genre: Computer. Description of the work, (preface) as well as reviews are available. Best literature library LitArk.com created for fans of good reading and offers a wide selection of genres:

Romance novel Science fiction Adventure Detective Science History Home and family Prose Art Politics Computer Non-fiction Religion Business Children Humor

Choose a favorite category and find really read worthwhile books. Enjoy immersion in the world of imagination, feel the emotions of the characters or learn something new for yourself, make an fascinating discovery.

Taieb Data analysis with Python : a modern approach
  • Book:
    Data analysis with Python : a modern approach
  • Author:
  • Publisher:
    Packt Publishing
  • Genre:
  • Year:
    2018
  • Rating:
    3 / 5
  • Favourites:
    Add to favourites
  • Your mark:
    • 60
    • 1
    • 2
    • 3
    • 4
    • 5

Data analysis with Python : a modern approach: summary, description and annotation

We offer to read an annotation, description, summary or preface (depends on what the author of the book "Data analysis with Python : a modern approach" wrote himself). If you haven't found the necessary information about the book — write in the comments, we will try to find it.

Taieb: author's other books


Who wrote Data analysis with Python : a modern approach? Find out the surname, the name of the author of the book and a list of all author's works by series.

Data analysis with Python : a modern approach — read online for free the complete book (whole text) full work

Below is the text of the book, divided by pages. System saving the place of the last page read, allows you to conveniently read the book "Data analysis with Python : a modern approach" online for free, without having to search again every time where you left off. Put a bookmark, and you can go to the page where you finished reading at any time.

Light

Font size:

Reset

Interval:

Bookmark:

Make
Data Analysis with Python Data Analysis with Python Copyright 2018 Packt - photo 1
Data Analysis with Python

Data Analysis with Python

Copyright 2018 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Acquisition Editors: Frank Pohlmann, Suresh M Jain

Project Editors: Savvy Sequeira, Kishor Rit

Content Development Editor: Alex Sorrentino

Technical Editor: Bhagyashree Rai

Proofreader: Safis Editing

Indexers: Priyanka Dhadke

Graphics: Tom Scaria

Production Coordinator: Sandip Tadge

First published: June 2018

Production reference: 1300718

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78883-996-9

www.packtpub.com

To Alexandra, Solomon, Zachary, Victoria and Charlotte:

Thank you for your support, unbounded love, and infinite patience. I would not have been able to complete this work without all of you.

To Fernand and Gisele:

Without whom I wouldn't be where I am today. Thank you for your continued guidance all these years.

maptio Mapt is an online digital library that gives you full access to over - photo 2

mapt.io

Mapt is an online digital library that gives you full access to over 5,000 books and videos, as well as industry leading tools to help you plan your personal development and advance your career. For more information, please visit our website.

Why subscribe?
  • Spend less time learning and more time coding with practical eBooks and Videos from over 4,000 industry professionals
  • Learn better with Skill Plans built especially for you
  • Get a free eBook or video every month
  • Mapt is fully searchable
  • Copy and paste, print, and bookmark content
PacktPub.com

Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at > for more details.

At www.PacktPub.com, you can also read a collection of free technical articles, sign up for a range of free newsletters, and receive exclusive discounts and offers on Packt books and eBooks.

Contributors
About the author

David Taieb is the Distinguished Engineer for the Watson and Cloud Platform Developer Advocacy team at IBM, leading a team of avid technologists on a mission to educate developers on the art of the possible with data science, AI and cloud technologies. He's passionate about building open source tools, such as the PixieDust Python Library for Jupyter Notebooks, which help improve developer productivity and democratize data science. David enjoys sharing his experience by speaking at conferences and meetups, where he likes to meet as many people as possible.

I want to give special thanks to all of the following dear friends at IBM who contributed to the development of PixieDust and/or provided invaluable support during the writing of this book: Brad Noble, Jose Barbosa, Mark Watson, Raj Singh, Mike Broberg, Jessica Mantaro, Margriet Groenendijk, Patrick Titzler, Glynn Bird, Teri Chadbourne, Bradley Holt, Adam Cox, Jamie Jennings, Terry Antony, Stephen Badolato, Terri Gerber, Peter May, Brady Paterson, Kathleen Francis, Dan O'Connor, Muhtar (Burak) Akbulut, Navneet Rao, Panos Karagiannis, Allen Dean, and Jim Young.

About the reviewers

Margriet Groenendijk is a data scientist and developer advocate for IBM. She has a background in climate research, where, at the University of Exeter, she explored large observational datasets and the output of global scale weather and climate models to understand the impact of land use on climate. Prior to that, she explored the effect of climate on the uptake of carbon from the atmosphere by forests during her PhD research at the Vrije Universiteit in Amsterdam.

Now adays, she explores ways to simplify working with diverse data using open source tools, IBM Cloud, and Watson Studio. She has experience with cloud services, databases, and APIs to access, combine, clean, and store different types of data. Margriet uses time series analysis, statistical data analysis, modeling and parameter optimisation, machine learning, and complex data visualization. She writes blogs and speaks about these topics at conferences and meetups.

va barbosa is a developer advocate for the Center for Open-Source Data & AI Technologies, where he helps developers discover and make use of data and machine learning technologies. This is fueled by his passion to help others, and guided by his enthusiasm for open source technology.

Always looking to embrace new challenges and fulfill his appetite for learning, va immerses himself in a wide range of technologies and activities. He has been an electronic technician, support engineer, software engineer, and developer advocate.

When not focusing on the developer experience, va enjoys dabbling in photography. If you can't find him in front of a computer, try looking behind a camera.

Packt is searching for authors like you

If you're interested in becoming an author for Packt, please visit authors.packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea.

Preface

"Developers are the most-important, most-valuable constituency in business today, regardless of industry."

-- Stephen O'Grady, author of The New Kingmakers

First, let me thank you and congratulate you, the reader, for the decision to invest some of your valuable time to read this book. Throughout the chapters to come, I will take you on a journey of discovering or even re-discovering data science from the perspective of a developer and will develop the theme of this book which is that data science is a team sport and that if it is to be successful, developers will have to play a bigger role in the near future and better collaborate with data scientists. However, to make data science more inclusive to people of all backgrounds and trades, we first need to democratize it by making data simple and accessible

Next page
Light

Font size:

Reset

Interval:

Bookmark:

Make

Similar books «Data analysis with Python : a modern approach»

Look at similar books to Data analysis with Python : a modern approach. We have selected literature similar in name and meaning in the hope of providing readers with more options to find new, interesting, not yet read works.


Reviews about «Data analysis with Python : a modern approach»

Discussion, reviews of the book Data analysis with Python : a modern approach and just readers' own opinions. Leave your comments, write what you think about the work, its meaning or the main characters. Specify what exactly you liked and what you didn't like, and why you think so.