In Deep
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Deep Learning
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.
Into the Deep
Charley Redford was just an ordinary girl until Jake Caplin moved to her small town in Indiana and convinced her she was extraordinary. Almost from day one Jake pulled Charley into the deep and promised he was right there with her. But when a tragic incident darkened Jake's life he waded out into the shallows and left Charley behind. Almost four years later Charley thinks she's moved on. That is until she takes a study year abroad in Edinburgh and bumps into none other than Jake Caplin at a party with his new girlfriend. The bad-boy-turned-good attempts to convince Charley to forgive him, and as her best friend starts spending time with Jake's, Charley calls a truce, only to find herself tumbling back into a friendship with him. As they grow closer, the spark between them flares and begins playing havoc with their lives and relationships. When jealousy and longing rear their destructive heads, Charley and Jake struggle to come to grips with what they mean to one another. And even if they work it out, there is no guarantee Charley will ever trust Jake to lead her back into the deep...
Regular Fabrics in Deep Sub-Micron Integrated-Circuit Design
Author: Fan Mo
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-05-08
Regular Fabrics in Deep Sub-Micron Integrated-Circuit Design discusses new approaches to better timing-closure and manufacturability of DSM Integrated Circuits. The key idea presented is the use of regular circuit and interconnect structures such that area/delay can be predicted with high accuracy. The co-design of structures and algorithms allows great opportunities for achieving better final results, thus closing the gap between IC and CAD designers. The regularities also provide simpler and possibly better manufacturability. In this book we present not only algorithms for solving particular sub-problems but also systematic ways of organizing different algorithms in a flow to solve the design problem as a whole. A timing-driven chip design flow is developed based on the new structures and their design algorithms, which produces faster chips in a shorter time.