Still going strong after more than a decade, the Los Angeles-based Machine Project is profiled in this encyclopedic book that explores unconventional ways of seeing and thinking about the world. New essays and images capture the quirky essence of Machine Project, where vacations for plants, concerts for dentists, and operas for dogs are a few of the typical offerings produced at the informal, non-profit, educational institution in Los Angeles. Designed in collaboration with Kimberly Varella, this book reflects on Machine Project's ongoing artistic practice, featuring an extensive selection of photographs of past projects and documentation of new performance projects at the Tang Museum by Haruko Tanaka, Krystal Krunch, Hana van der Kolk, Carmina Escobar, Kamau Patton, Dawn Kasper, Joshua Beckman, Asher Hartman, and Chris Kallmyer among others.

In The Portrait Machine Project, Brooklyn-based New Zealand photographer Carlo Van de Roer (born 1975) explores the idea that a camera can reveal otherwise hidden facets of a subject's character, and their relationship with the photographer and viewer. Van de Roer uses a Polaroid aura camera, developed in the 1970s in an attempt to record what a psychic might see. His subjects--friends, family, artists Miranda July, Terence Koh and Aurel Schmidt, author James Frey--are connected by sensors to the camera, which translates biofeedback into information about their characters and how they are viewed. The camera depicts this information as color in the Polaroid and as a printed description and diagram. In this, his first book, Van de Roer prompts us to question what we expect from a portrait, particularly when it's of someone we think we know.

A fascinating examination of technological utopianism and its complicated consequences. In The Charisma Machine, Morgan Ames chronicles the life and legacy of the One Laptop per Child project and explains why—despite its failures—the same utopian visions that inspired OLPC still motivate other projects trying to use technology to “disrupt” education and development. Announced in 2005 by MIT Media Lab cofounder Nicholas Negroponte, One Laptop per Child promised to transform the lives of children across the Global South with a small, sturdy, and cheap laptop computer, powered by a hand crank. In reality, the project fell short in many ways—starting with the hand crank, which never materialized. Yet the project remained charismatic to many who were captivated by its claims of access to educational opportunities previously out of reach. Behind its promises, OLPC, like many technology projects that make similarly grand claims, had a fundamentally flawed vision of who the computer was made for and what role technology should play in learning. Drawing on fifty years of history and a seven-month study of a model OLPC project in Paraguay, Ames reveals that the laptops were not only frustrating to use, easy to break, and hard to repair, they were designed for “technically precocious boys”—idealized younger versions of the developers themselves—rather than the children who were actually using them. The Charisma Machine offers a cautionary tale about the allure of technology hype and the problems that result when utopian dreams drive technology development.

Tracy Kidder's "riveting" (Washington Post) story of one company's efforts to bring a new microcomputer to market won both the Pulitzer Prize and the National Book Award and has become essential reading for understanding the history of the American tech industry. Computers have changed since 1981, when The Soul of a New Machine first examined the culture of the computer revolution. What has not changed is the feverish pace of the high-tech industry, the go-for-broke approach to business that has caused so many computer companies to win big (or go belly up), and the cult of pursuing mind-bending technological innovations. The Soul of a New Machine is an essential chapter in the history of the machine that revolutionized the world in the twentieth century. "Fascinating...A surprisingly gripping account of people at work." --Wall Street Journal

Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on book, you’ll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers—including experienced practitioners and novices alike—will learn the tools, best practices, and challenges involved in building a real-world ML application step by step. Author Emmanuel Ameisen, an experienced data scientist who led an AI education program, demonstrates practical ML concepts using code snippets, illustrations, screenshots, and interviews with industry leaders. Part I teaches you how to plan an ML application and measure success. Part II explains how to build a working ML model. Part III demonstrates ways to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies. This book will help you: Define your product goal and set up a machine learning problem Build your first end-to-end pipeline quickly and acquire an initial dataset Train and evaluate your ML models and address performance bottlenecks Deploy and monitor your models in a production environment

With 35 projects that you'll love to make and a helpful techniques section, this book will teach you all about sewing machines. Start out with Clothes and Accessories, where you can make a felt collar and cosy scarf, as well as a pretty skirt.

Broken Time Machines: Daisy Patton, designed by Joshua Gamma and edited by Yasmeen Siddiqui, is comprised of writings by award-winning Irish poet and novelist Elaine Feeney; celebrated American poet Sommer Browning; British scholar Salma Ahmad Caller; French feminist literary critic Adèle Cassigneul; American historian William Max Nelson; and American critic Kealey Boyd. Together these contributors have created a sensitively designed book that behaves as a way-finding device for interpreting the work of emerging artist Daisy Patton.

The only way to learn is to practice! In Machine Learning Bookcamp, you''ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you''ve learned in previous chapters. By the end of the bookcamp, you''ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technology Machine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that''s exactly what you''ll be doing in Machine Learning Bookcamp. about the book In Machine Learning Bookcamp you''ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you''ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You''ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you''re done working through these fun and informative projects, you''ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what''s inside Code fundamental ML algorithms from scratch Collect and clean data for training models Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images and text Deploy ML models to a production-ready environment about the reader For readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning.

Inspired by a brother's high school science project--a perpetual motion machine that could save the world-- The Perpetual Motion Machine is a memoir in essays that attempts to save a sibling by depicting the visceral pain that accompanies longing for some past impossibility. The collection has been a science project in its study of memory, in the calculation and plotting of the moments that make up a childhood. The preparation has been "in the field" in that it is built upon the gathering of lived experience; the evidence is photo albums, family interviews, and anecdotes from friends. The project has been one giant experiment--to see if they can all make it out alive.

This book by Diana Levine Knits features 25 patterns to make using the Addi Express Kingsize knitting machine, the Addi Express 22 needle knitting machine, the Sentro 48 needle knitting machine, the Sentro 40 needle knitting machine, and I-Cord knitting machines. The book includes patterns for hats, purses, pencil bags, stuffed animals, blankets, scarves & more. The beginning of the book features a section introducing how to use circular knitting machines, some common techniques for seaming and assembling pieces made with circular knitting machines, and an introduction to the various machines that are available on the market. Circular knitting machines are a quick and fun way to create beautiful knitted items. Video tutorials: youtube.com/dianalevineknits Learn more: dianalevineknits.com instagram.com/dianalevineknits