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Data Science Live Book

Author: Pablo Casas

Publisher:

Published: 2018-03-16

Total Pages:

ISBN-13: 9789874273666

This book is a practical guide to problems that commonly arise when developing a machine learning project. The book's topics are: Exploratory data analysis Data Preparation Selecting best variables Assessing Model Performance More information on predictive modeling will be included soon. This book tries to demonstrate what it says with short and well-explained examples. This is valid for both theoretical and practical aspects (through comments in the code). This book, as well as the development of a data project, is not linear. The chapters are related among them. For example, the missing values chapter can lead to the cardinality reduction in categorical variables. Or you can read the data type chapter and then change the way you deal with missing values. You¿ll find references to other websites so you can expand your study, this book is just another step in the learning journey. It's open-source and can be found at http://livebook.datascienceheroes.com

Big Data

Author: Viktor Mayer-Schönberger

Publisher: Houghton Mifflin Harcourt

Published: 2013

Total Pages: 257

ISBN-13: 0544002695

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A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.

Collecting Lives

Author: Elizabeth Rodrigues

Publisher: University of Michigan Press

Published: 2022-05-16

Total Pages: 239

ISBN-13: 0472902636

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On a near-daily basis, data is being used to narrate our lives. Categorizing algorithms drawn from amassed personal data to assign narrative destinies to individuals at crucial junctures, simultaneously predicting and shaping the paths of our lives. Data is commonly assumed to bring us closer to objectivity, but the narrative paths these algorithms assign seem, more often than not, to replicate biases about who an individual is and could become. While the social effects of such algorithmic logics seem new and newly urgent to consider, Collecting Lives looks to the late nineteenth and early twentieth century U.S. to provide an instructive prehistory to the underlying question of the relationship between data, life, and narrative. Rodrigues contextualizes the application of data collection to human selfhood in order to uncover a modernist aesthetic of data that offers an alternative to the algorithmic logic pervading our sense of data’s revelatory potential. Examining the work of W. E. B. Du Bois, Henry Adams, Gertrude Stein, and Ida B. Wells-Barnett, Rodrigues asks how each of these authors draw from their work in sociology, history, psychology, and journalism to formulate a critical data aesthetic as they attempt to answer questions of identity around race, gender, and nation both in their research and their life writing. These data-driven modernists not only tell different life stories with data, they tell life stories differently because of data.

Recurrent Events Data Analysis for Product Repairs, Disease Recurrences, and Other Applications

Author: Wayne B. Nelson

Publisher: SIAM

Published: 2003-01-01

Total Pages: 157

ISBN-13: 0898715229

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Survival data consist of a single event for each population unit, namely, end of life, which is modeled with a life distribution. However, many applications involve repeated-events data, where a unit may accumulate numerous events over time. This applied book provides practitioners with basic nonparametric methods for such data.

Dear Data

Author: Giorgia Lupi

Publisher: Chronicle Books

Published: 2016-09-13

Total Pages: 304

ISBN-13: 1616895462

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Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.

Data Analysis for the Life Sciences with R

Author: Rafael A. Irizarry

Publisher: CRC Press

Published: 2016-10-04

Total Pages: 461

ISBN-13: 1498775861

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This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.

Storytelling with Data

Author: Cole Nussbaumer Knaflic

Publisher: John Wiley & Sons

Published: 2015-10-09

Total Pages: 288

ISBN-13: 1119002265

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Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!