Data-ism - The Revolution Transforming Decision Making Consumer Behavior and Almost Everything Else

Steve Lohr

Summary

“Lohr uses his Pulitzer Prize-winning reporting skills to dig into and explain the power, pervasiveness, and potential downside of big data.” —Library Journal

In Data-ism, New York Times reporter Steve Lohr explains how big-data technology is ushering in a revolution in proportions that promise to be the basis of the next wave of efficiency and innovation across the economy. But more is at work here than technology. Big data is also the vehicle for a point of view, or philosophy, about how decisions will be—and perhaps should be—made in the future. Lohr investigates the benefits of data while also examining its dark side.

Data-ism is about this next phase, in which vast Internet-scale data sets are used for discovery and prediction in virtually every field. It shows how this new revolution will change decision making—by relying more on data and analysis, and less on intuition and experience—and transform the nature of leadership and management. Focusing on young entrepreneurs at the forefront of data science as well as on giant companies such as IBM that are making big bets on data science for the future of their businesses, Data-ism is a field guide to what is ahead, explaining how individuals and institutions will need to exploit, protect, and manage data to stay competitive in the coming years. With rich examples of how the rise of big data is affecting everyday life, Data-ism also raises provocative questions about policy and practice that have wide implications for everyone.

The age of data-ism is here. But are we ready to handle its consequences, good and bad?

Available since: 03/10/2015.

Print length: 261 pages.

Other books that might interest you

Urban Policy and Governance -...

Lyric Vale

Urban policy and governance are central to shaping the future of cities worldwide. As urban areas continue to expand, the challenges faced by city leaders, policymakers, and residents grow ever more complex. Urban policy refers to the strategies, frameworks, and regulations that guide the development and management of cities. It encompasses everything from housing and infrastructure to social equity, environmental sustainability, and economic growth. Governance, on the other hand, focuses on the decision-making processes, institutions, and actors responsible for implementing these policies. Effective urban governance ensures that cities function smoothly and equitably while addressing the diverse needs of their populations. 
The rapid pace of urbanization has been a defining feature of the 21st century, with over half of the world's population now living in cities. This urban shift presents numerous challenges, including overcrowding, resource scarcity, environmental degradation, and social inequality. However, it also creates opportunities for innovation and progress. A well-crafted urban policy can harness the potential of urbanization to improve quality of life, create economic opportunities, and foster sustainability. 
Urban governance is shaped by various factors, including political, economic, and social dynamics. At its core, it involves coordinating efforts among multiple stakeholders, such as local governments, private sector entities, civil society groups, and international organizations. The collaboration between these actors is crucial to addressing the complex and interconnected issues that cities face. Effective governance must be inclusive, transparent, and accountable to ensure that all voices, particularly those of marginalized communities, are heard and considered in decision-making processes.

Show book

The Snake and the Salamander -...

Alvin R. Breisch

A beautifully illustrated tour of the region’s snakes, lizards, turtles, frogs, and salamanders.

In the best tradition of natural history writing and art, The Snake and the Salamander explores the diverse collection of reptiles and amphibians that inhabit the northeastern quadrant of the United States. Covering thirteen states that run from Maine to Virginia, author Alvin R. Breisch and artist Matt Patterson showcase the lives of 83 species of snakes, lizards, turtles, frogs, and salamanders. These intriguing animals are organized by habitat and type, from forest to grassland to bogs to big waters, and revealed through a combination of Breisch’s engaging prose and Patterson’s original color illustrations.

Breisch’s guided tour combines historical notes and conservation issues with lessons on genetics, evolution, habitats, life histories, and more. Discover how careful attention to frog calls coupled with DNA analysis led to the discovery of a new species of frog in New York City, why evolutionary adaptations made the Eastern Ratsnake a superb climber, and the surprising fact that Spiny Softshell turtles actually sprint on land to retreat from predators. Breisch also tells the odd tale of the Green Frog and the Smooth Greensnake, two “green species” that do not actually have any green pigment in their skin. Every species has a story to tell?one that will keep the reader wanting to learn more.

The breadth of herpetofauna in the area will surprise many readers: more than 8% of the world’s salamanders and 11% of all turtle species live in the region. Beyond numbers, however, lie aesthetics. The surprising colors and fascinating lifestyles of the reptile and amphibian species in this book will mesmerize readers young and old.

Winner of the National Outdoor Book Award of the NOBA Foundation (Nature and Environment Category)

“The breadth of herpetofauna in the area will surprise many readers: more than 8% of the world’s salamanders and 11% of all turtle species live in the region. Beyond numbers, however, lie aesthetics. The surprising colors and fascinating lifestyles of the reptile and amphibian species in this book will mesmerize readers young and old.” —The Birdbooker Report

“While most field guides are organized by species, this book is more than a field guide; it places the animals in the context of their environment.” —The Altamont Enterprise

Show book

Statistical Analysis for...

Daniel Garfield

Dive into the fascinating realm of data with "Statistical Analysis for Beginners: A Hands-On Approach to Unraveling Data Mysteries and Transforming Numbers into Knowledge." This comprehensive guide is crafted for those seeking to demystify the world of statistics and harness the power of data in their hands.

Show book

The Travels of Sir John Mandeville

John Mandeville

The Travels of Sir John Mandeville. Itinerarium

libreka classics – These are classics of literary history, reissued and made available to a wide audience. 
Immerse yourself in well-known and popular titles!

Show book

Stuck - How Vaccine Rumors Start...

Heidi J. Larson

Vaccine reluctance and refusal are no longer limited to the margins of society. Debates around vaccines' necessity—along with questions around their side effects—have gone mainstream, blending with geopolitical conflicts, political campaigns, celebrity causes, and "natural" lifestyles to win a growing number of hearts and minds. Today's anti-vaccine positions find audiences where they've never existed previously. 
 
 
 
Stuck examines how the issues surrounding vaccine hesitancy are, more than anything, about people feeling left out of the conversation. A new dialogue is long overdue, one that addresses the many types of vaccine hesitancy and the social factors that perpetuate them. To do this, Stuck provides a clear-eyed examination of the social vectors that transmit vaccine rumors, their manifestations around the globe, and how these individual threads are all connected.

Show book

Hands-on ML Projects with OpenCV

Mugesh S.

Be at your A game in building Intelligent systems by leveraging Computer vision and Machine Learning.

KEY FEATURES
- Step-by-step instructions and code snippets for real world ML projects.
- Covers entire spectrum from basics to advanced concepts such as deep learning, transfer learning, and model optimization
- Loaded with practical tips and best practices for implementing machine learning with OpenCV for optimising your workflow.

DESCRIPTION
This book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in a step-by-step manner using code and output snippets.

Hands-on projects with real-world datasets will offer you an invaluable experience in solving OpenCV challenges with machine learning. It’s an ultimate guide to explore areas like deep learning, transfer learning, and model optimization, empowering readers to tackle complex tasks. Every chapter offers practical tips and tricks to build effective ML models.

By the end, you would have mastered and applied ML concepts confidently to real-world computer vision problems and will be able to develop robust and accurate machine-learning models for diverse applications.

Whether you are new to machine learning or seeking to enhance your computer vision skills, This book is an invaluable resource for mastering the integration of machine learning and computer vision using OpenCV and Python.

WHAT WILL YOU LEARN
- Learn how to work with images and perform basic image processing tasks using OpenCV.
- Implement machine learning techniques to computer vision tasks such as image classification, object detection, and image segmentation.
- Work on real-world projects and datasets to gain hands-on experience in applying machine learning techniques with OpenCV.
- Explore the concepts of deep learning using Tensorflow and Keras and how it can be used for computer vision tasks.
- Understand the concept of transfer learning and how pre-trained models can be leveraged for new tasks.
- Utilize techniques for model optimization and deployment in resource-constrained environments.
- Implement end-to-end solutions and address challenges encountered in practical scenarios.

WHO IS THIS BOOK FOR?
This book is for everyone with a basic understanding of programming and who wants to apply machine learning in computer vision using OpenCV and Python. Whether you're a student, researcher, or developer, this book will equip you with practical skills for machine learning projects. Some familiarity with Python and machine learning concepts is assumed. Beginners too will find this book valuable as it offers clear examples and explanations for every concept.

TABLE OF CONTENTS
Chapter 1: Getting Started With OpenCV
Chapter 2: Basic Image & Video Analytics in OpenCV
Chapter 3: Image Processing 1 using OpenCV
Chapter 4: Image Processing 2 using OpenCV
Chapter 5: Thresholding and Contour Techniques Using OpenCV
Chapter 6: Detect Corners and Road Lane using OpenCV
Chapter 7: Object And Motion Detection Using Opencv
Chapter 8: Image Segmentation and Detecting Faces Using OpenCV
Chapter 9: Introduction to Deep Learning with OpenCV
Chapter 10: Advance Deep Learning Projects with OpenCV
Chapter 11: Deployment of OpenCV projects

Show book