Code Of Massachusetts Regulations 2015
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Total Pages | : 72 |
Release | : 2015 |
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Archival snapshot of entire looseleaf Code of Massachusetts Regulations held by the Social Law Library of Massachusetts as of January 2020.
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Total Pages | : 2 |
Release | : 2016 |
Genre | : Administrative law |
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Archival snapshot of entire looseleaf Code of Massachusetts Regulations held by the Social Law Library of Massachusetts as of January 2016.
Author | : International Code Council |
Publisher | : International Code Council |
Total Pages | : 0 |
Release | : 2014 |
Genre | : Building |
ISBN | : 9781609834678 |
Offers the latest regulations on designing and installing commercial and residential buildings.
Author | : International Code Council |
Publisher | : |
Total Pages | : 0 |
Release | : 2014-06-12 |
Genre | : Building laws |
ISBN | : 9781609834784 |
For the most current mechanical codes that address the design and installation of the most current mechanical systems, use the 2015 INTERNATIONAL MECHANICAL CODE SOFT COVER. Designed to provide comprehensive regulations for mechanical systems and equipment, it includes coverage of HVAC, exhaust systems, chimneys and vents, ducts, appliances, boilers, water heaters, refrigerators, hydronic piping, and solar systems. This valuable reference uses prescriptive- and performance- related provisions to establish minimum regulations for a variety of systems. This updated code includes information on condensate pumps, and the ventilation system for enclosed parking garages.
Author | : United States. Congress |
Publisher | : |
Total Pages | : 1324 |
Release | : 1968 |
Genre | : Law |
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Author | : International Code Council |
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Total Pages | : 0 |
Release | : 2014-06-11 |
Genre | : Building |
ISBN | : 9781609834715 |
Resource added for the Fire Science Program 305318.
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Total Pages | : 273 |
Release | : 2016 |
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Archival snapshot of entire looseleaf Code of Massachusetts Regulations held by the Social Law Library of Massachusetts as of January 2020.
Author | : MaryAnn Neary |
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Total Pages | : |
Release | : 2002 |
Genre | : Legal research |
ISBN | : 9781575892764 |
Author | : Alison Green |
Publisher | : Ballantine Books |
Total Pages | : 306 |
Release | : 2018-05-01 |
Genre | : Business & Economics |
ISBN | : 0399181822 |
From the creator of the popular website Ask a Manager and New York’s work-advice columnist comes a witty, practical guide to 200 difficult professional conversations—featuring all-new advice! There’s a reason Alison Green has been called “the Dear Abby of the work world.” Ten years as a workplace-advice columnist have taught her that people avoid awkward conversations in the office because they simply don’t know what to say. Thankfully, Green does—and in this incredibly helpful book, she tackles the tough discussions you may need to have during your career. You’ll learn what to say when • coworkers push their work on you—then take credit for it • you accidentally trash-talk someone in an email then hit “reply all” • you’re being micromanaged—or not being managed at all • you catch a colleague in a lie • your boss seems unhappy with your work • your cubemate’s loud speakerphone is making you homicidal • you got drunk at the holiday party Praise for Ask a Manager “A must-read for anyone who works . . . [Alison Green’s] advice boils down to the idea that you should be professional (even when others are not) and that communicating in a straightforward manner with candor and kindness will get you far, no matter where you work.”—Booklist (starred review) “The author’s friendly, warm, no-nonsense writing is a pleasure to read, and her advice can be widely applied to relationships in all areas of readers’ lives. Ideal for anyone new to the job market or new to management, or anyone hoping to improve their work experience.”—Library Journal (starred review) “I am a huge fan of Alison Green’s Ask a Manager column. This book is even better. It teaches us how to deal with many of the most vexing big and little problems in our workplaces—and to do so with grace, confidence, and a sense of humor.”—Robert Sutton, Stanford professor and author of The No Asshole Rule and The Asshole Survival Guide “Ask a Manager is the ultimate playbook for navigating the traditional workforce in a diplomatic but firm way.”—Erin Lowry, author of Broke Millennial: Stop Scraping By and Get Your Financial Life Together
Author | : Ian Goodfellow |
Publisher | : MIT Press |
Total Pages | : 801 |
Release | : 2016-11-10 |
Genre | : Computers |
ISBN | : 0262337371 |
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.