数学与深度学习架构 MEAP V02
关于
作者
Krishnendu Chaudhury & Ananya Ashok, Sujay Narumanchi & Devashish Shankar
译者
Google翻译
译文摘抄
1 An overview of machine learning and deep learning
1 机器学习和深度学习概述
Deep learning has transformed computer vision, natural language and speech processing in particular and artificial intelligence in general. From a bag of semi-discordant tricks, none of which worked satisfactorily on a real life problem, artificial intelligence has become a formidable tool to solve real problems faced by industry, at scale. This is nothing short of a revolution going on under our very noses. If one wants to lead the curve of this revolution, it is imperative to understand the underlying principles and abstractions, rather than simply memorizing the “how to” steps of some hands on guide. This is where the mathematics comes in.
深度学习改变了计算机视觉、自然语言和语音处理，特别是人工智能。人工智能从一堆半不一致的技巧（其中没有一个能够令人满意地解决现实生活中的问题）变成了大规模解决工业面临的实际问题的强大工具。这无异于一场在我们眼皮底下进行的革命。如果一个人想引领这场革命，就必须了解基本原理和抽象概念，而不是简单地记住一些实践指南中的“如何做”步骤。这就是数学的用武之地。
In this first chapter we will give an overview of deep learning. This will require us to use some concepts that have been explained in subsequent chapters. The reader should not worry if there are some open questions at the end of this chapter. This chapter is aimed at orienting one’s mind towards this difficult subject. As individual concepts get clearer in subsequent chapters, the reader should consider coming back and giving this chapter a re-read.
在第一章中，我们将概述深度学习。这将需要我们使用后续章节中解释的一些概念。读者不必担心本章末尾是否存在一些悬而未决的问题。本章旨在将人们的思想引导到这个困难的主题上。随着后续章节中的各个概念变得更加清晰，读者应该考虑回来重新阅读本章。
1.1 A first look at machine/deep learning - a paradigm shift in computation
1.1 机器/深度学习初探——计算范式转变
Making decisions and/or predictions is a central requirement of life. This essentially involves taking in a set of sensory or knowledge inputs and generating decisions or estimates by processing them.
做出决定和/或预测是生活的核心要求。这本质上涉及接收一组感官或知识输入并通过处理它们来生成决策或估计。
For instance, a cat’s brain is often trying to choose between the following options: run away from the object in front vs ignore the object in front vs approach the object in front and purr. It makes that decision by processing sensory inputs, like perceived hardness of the object in front, perceived sharpness of the object in front, etc. This is an instance of classification problem where the output is one out of a set of possible classes.
例如，猫的大脑经常尝试在以下选项之间进行选择：逃离前面的物体、忽略前面的物体、接近前面的物体并发出咕噜声。它通过处理感官输入来做出决定，例如感知到的前方物体的硬度、感知到的前方物体的清晰度等。这是分类问题的一个实例，其中输出是一组可能类别中的一个。