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所在平台: Udemy |
课程主页: https://www.udemy.com/course/vsd-machine-intelligence-in-eda-cad/
课程评论：没有评论
**课程名称：** VSD - 电子设计自动化/计算机辅助设计中的机器学习 **课程概述：** 本课程是一个在线研讨会（2018年3月31日）的总结，由Paripath Inc.的CEO Rohit主讲。课程首先介绍了电子设计自动化（EDA）和机器学习（ML）的基本概念。随后，课程详细探讨了机器学习的分类，包括监督学习和无监督学习，并对其进行深入阐述。 接着，课程重点介绍了当前可用的机器学习框架，包括通用框架、大数据处理框架以及深度学习框架，并讨论了哪种框架最适合设计自动化。课程将机器学习与CAD、EDA及VLSI流程紧密结合。 课程还详细讲解了“应用理论”方面的内容，包括数据集、数据分析（如数据增强、探索性数据分析、归一化、随机化）、术语解释以及开发解决方案的流程。这部分内容侧重于当公司希望在其产品中引入机器学习功能时，应采取的步骤和解决方案流程，并将其称为“飞行理论的前导”。 随后，课程深入讲解了监督学习中的回归方法，并提供了两个实际案例：电阻估算和多项式回归（用于电容估算）。其中，电阻估算的案例使用了20nm技术的数据集。 最后，课程还介绍了如何运用逻辑回归创建线性分类器，以及如何进行降维（即如何减小大型数据集的规模，使其能在笔记本电脑甚至手机上运行），并提供了一个相关的实际案例。需要注意的是，课程中涉及的数学原理将不包含在研讨会内容中。 **讲师简介：** Rohit Sharma是Paripath Inc.的创始人兼CEO，该公司位于加州Milpitas。他毕业于印度理工学院德里分校（IIT Delhi），著有两本书，并在国际会议和期刊上发表了多篇论文。他在电子设计自动化领域拥有超过20年的经验，致力于学习、改进和设计解决方案。他热衷于机器学习、分析、特性描述和建模等多个技术领域，并因此构思和创建了guna——一款针对现代工艺流程的先进特性描述软件。他目前在Paripath Inc.任职。
This webinar was conducted on 31st March 2018 with Rohit, CEO Paripath Inc.We start with Electronic design automation and what is machine learning. Then we will give overall introduction to categories of machine learning (supervised and unsupervised learning) and go about discussing that a little bit. Then we talk about the frameworks which are available today, like general purpose, big data processing and deep-learning, and which one is suitable for design automation. This is Machine Learning in general with a focus on CAD, EDA and VLSI flows. Then we talk about Applied Theory (data sets, data analysis like data augmentation, exploratory data analysis, normalization, randomization), as to what are the terms and terminologies and what do we do with that, accuracy, how do we develop the algorithm, essentially the things that are required to develop the solution flow, lets say, you as the company wants to add a feature in your product using machine learning, what you would be doing, and what your flow will look like and this is what is shown as pre-cursor of flight theory as what you should be looking out. And then we start with regression, which is first in supervised learning. In the regression, we will give couple of example, like first is resistance estimation, second is polynomial regression which is capacitance estimation. For resistance estimation, we have the dataset from 20nm technology. And finally, we go on to create a linear classifier using logistic regression. Next will be dimensionality reduction, meaning, you have a large dataset and how to you reduce the size of that so that you can run on a laptop or even on your cell phone. Then there is a big example of that. Everything has mathematics behind that, this wont be a part of the webinar.About Rohit - Rohit Sharma is Founder and CEO of Paripath Inc based in Milpitas, CA. He graduated from IIT Delhi.He has authored 2 books and published several papers in international conferences and journals. He has contributed to electronic design automation domain for over 20 years learning, improvising and designing solutions. He is passionate about many technical topics including Machine Learning, Analysis, Characterization and Modeling, which led him to architect guna - an advanced characterization software for modern nodes.He currently works for Paripath Inc.
