Hard Code
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I.M. Wright's Hard Code
Get the brutal truth about coding, testing, and project management—from a Microsoft insider who tells it like it is. I. M. Wright's deliberately provocative column "Hard Code" has been sparking debate amongst thousands of engineers at Microsoft for years. And now (despite our better instincts), we're making his opinions available to everyone. In this collection of over 80 columns, Eric Brechner's alter ego pulls no punches with his candid commentary and best practice solutions to the issues that irk him the most. He dissects the development process, examines tough team issues, and critiques how the software business is run, with the added touch of clever humor and sardonic wit. His ideas aren't always popular (not that he cares), but they do stimulate discussion and imagination needed to drive software excellence. Get the unvarnished truth on how to: Improve software quality and value—from design to security Realistically manage project schedules, risks, and specs Trim the fat from common development inefficiencies Apply process improvement methods—without being an inflexible fanatic Drive your own successful, satisfying career Don't be a dictator—develop and manage a thriving team! Companion Web site includes: Agile process documents Checklists, templates, and other resources
Smarter Data Science
Organizations can make data science a repeatable, predictable tool, which business professionals use to get more value from their data Enterprise data and AI projects are often scattershot, underbaked, siloed, and not adaptable to predictable business changes. As a result, the vast majority fail. These expensive quagmires can be avoided, and this book explains precisely how. Data science is emerging as a hands-on tool for not just data scientists, but business professionals as well. Managers, directors, IT leaders, and analysts must expand their use of data science capabilities for the organization to stay competitive. Smarter Data Science helps them achieve their enterprise-grade data projects and AI goals. It serves as a guide to building a robust and comprehensive information architecture program that enables sustainable and scalable AI deployments. When an organization manages its data effectively, its data science program becomes a fully scalable function that’s both prescriptive and repeatable. With an understanding of data science principles, practitioners are also empowered to lead their organizations in establishing and deploying viable AI. They employ the tools of machine learning, deep learning, and AI to extract greater value from data for the benefit of the enterprise. By following a ladder framework that promotes prescriptive capabilities, organizations can make data science accessible to a range of team members, democratizing data science throughout the organization. Companies that collect, organize, and analyze data can move forward to additional data science achievements: Improving time-to-value with infused AI models for common use cases Optimizing knowledge work and business processes Utilizing AI-based business intelligence and data visualization Establishing a data topology to support general or highly specialized needs Successfully completing AI projects in a predictable manner Coordinating the use of AI from any compute node. From inner edges to outer edges: cloud, fog, and mist computing When they climb the ladder presented in this book, businesspeople and data scientists alike will be able to improve and foster repeatable capabilities. They will have the knowledge to maximize their AI and data assets for the benefit of their organizations.
How To Use Automotive Diagnostic Scanners
From hand-held, dedicated units to software that turns PCs and Palm Pilots into powerful diagnostic scanners, auto enthusiasts today have a variety of methods available to make use of on-board diagnostic systems. And not only can they be used to diagnose operational faults, they can be used as low-budget data acquistion systems and dynamometers, so you can maximize your vehicle's performance. Beginning with why scanners are needed to work effectively on modern cars, this book teaches you how to choose the right scanner for your application, how to use the tool, and what each code means. "How To Use Automotive Diagnostic Scanners" is illustrated with photos and diagrams to help you understand OBD-I and OBD-II systems (including CAN) and the scanners that read the information they record. Also included is a comprehensive list of codes and what they mean. From catalytic converters and O2 sensors to emissions and automotive detective work, this is the complete reference for keeping your vehicle EPA-compliant and on the road!