“Amy Webb found her true love after a search that's both charmingly romantic and relentlessly data-driven. Anyone who uses online dating sites must read her funny, fascinating book.”—Gretchen Rubin, #1 New York Times bestselling author of The Happiness Project After yet another disastrous date, Amy Webb was preparing to cancel her JDate membership when epiphany struck: her standards weren’t too high, she just wasn’t approaching the process the right way. Using her gift for data strategy, she found which keywords were digital-man magnets, analyzed photos, and then adjusted her (female) profile to make the most of that intel. Then began the deluge—dozens of men who actually met her own stringent requirements wanted to meet her. Among them: her future husband, now the father of her child.

Martys second book, My Love Story: Book of Poetry, will move, touch, and inspire you to find your creative self through his wisdom. He wrote 110 poems in three months, feeling an extraordinary waterfall of energy flowing through him that was channeled from spirit. The book is divided into six areas of life: love, inspiration, gratitude, wisdom, joy, and peace. By reading this book, you will understand the meaning of life and find the purpose of why you are here and what its all about. My Love Story: Book of Poetry is all about love. The book will give you a road map of experiences to teach you to go deeper into your lifeto have the most creative life possible. What this book is really telling you is to have fun in your life. Its all about having fun. Whatever negative experiences we all have had, turn them into a positive lifestyle for yourself. We all have a choicecome from love or come from fear. Please spread love to yourself and others. Love, blessings, and gratitude, Marty Cole

“Amy Webb found her true love after a search that's both charmingly romantic and relentlessly data-driven. Anyone who uses online dating sites must read her funny, fascinating book.”—Gretchen Rubin, #1 New York Times bestselling author of The Happiness Project After yet another disastrous date, Amy Webb was preparing to cancel her JDate membership when epiphany struck: her standards weren’t too high, she just wasn’t approaching the process the right way. Using her gift for data strategy, she found which keywords were digital-man magnets, analyzed photos, and then adjusted her (female) profile to make the most of that intel. Then began the deluge—dozens of men who actually met her own stringent requirements wanted to meet her. Among them: her future husband, now the father of her child.

After a half century of battling for gender equality, women have been freed from the necessity of securing a husband for economic stability, sexual fulfillment, or procreation. Marriage is a choice, and increasingly women (and men) are opting out. Yet despite these changes, the cultural power of marriage has burgeoned. What was once an obligation has become an exclusive club into which heterosexual women with the right amount of self-discipline may win entry. The newly exalted professionalized wife is no longer reliant on her husband’s status or money; instead she can wield her own power provided she can successfully manage the business of being a wife. Wife, Inc. tells a fiercely contemporary story revealing that today’s wives do not labor in the home. Instead, the work of wifedom occurs in online dating sites, on reality television, in social media, and on the campaign trail. No longer the stuff of marriage vows, these realms are now controlled by brand management and marketability. To prosper, women must appear confident, empowered, and sexually savvy. Suzanne Leonard follows women as they date, prepare to wed, and toil as wives, using examples from popular culture in order to reveal marriage's newly professionalized role in the lives of American women. Being a wife is a business that takes a lot more than a vow to maintain.

As the availability of high-throughput data-collection technologies, such as information-sensing mobile devices, remote sensing, internet log records, and wireless sensor networks has grown, science, engineering, and business have rapidly transitioned from striving to develop information from scant data to a situation in which the challenge is now that the amount of information exceeds a human's ability to examine, let alone absorb, it. Data sets are increasingly complex, and this potentially increases the problems associated with such concerns as missing information and other quality concerns, data heterogeneity, and differing data formats. The nation's ability to make use of data depends heavily on the availability of a workforce that is properly trained and ready to tackle high-need areas. Training students to be capable in exploiting big data requires experience with statistical analysis, machine learning, and computational infrastructure that permits the real problems associated with massive data to be revealed and, ultimately, addressed. Analysis of big data requires cross-disciplinary skills, including the ability to make modeling decisions while balancing trade-offs between optimization and approximation, all while being attentive to useful metrics and system robustness. To develop those skills in students, it is important to identify whom to teach, that is, the educational background, experience, and characteristics of a prospective data-science student; what to teach, that is, the technical and practical content that should be taught to the student; and how to teach, that is, the structure and organization of a data-science program. Training Students to Extract Value from Big Data summarizes a workshop convened in April 2014 by the National Research Council's Committee on Applied and Theoretical Statistics to explore how best to train students to use big data. The workshop explored the need for training and curricula and coursework that should be included. One impetus for the workshop was the current fragmented view of what is meant by analysis of big data, data analytics, or data science. New graduate programs are introduced regularly, and they have their own notions of what is meant by those terms and, most important, of what students need to know to be proficient in data-intensive work. This report provides a variety of perspectives about those elements and about their integration into courses and curricula.

Intelligence services, government administrations, businesses, and a growing majority of the population are hooked on the idea that big data can reveal patterns and correlations in everyday life. Initiated by software engineers and carried out through algorithms, the mining of big data has sparked a silent revolution. But algorithmic analysis and data mining are not simply byproducts of media development or the logical consequences of computation. They are the radicalization of the Enlightenment's quest for knowledge and progress. Data Love argues that the "cold civil war" of big data is taking place not among citizens or between the citizen and government but within each of us. Roberto Simanowski elaborates on the changes data love has brought to the human condition while exploring the entanglements of those who—out of stinginess, convenience, ignorance, narcissism, or passion—contribute to the amassing of ever more data about their lives, leading to the statistical evaluation and individual profiling of their selves. Writing from a philosophical standpoint, Simanowski illustrates the social implications of technological development and retrieves the concepts, events, and cultural artifacts of past centuries to help decode the programming of our present.