Lecture 5: Gaussian Discriminant Analysis, Naive Bayes and EM Algorithm Feng Li Shandong University fli@sdu.edu.cn September 27, 2023 Feng Li (SDU) GDA, NB and EM September 27, 2023 1 / 122 Outline Outline 1 Probability Theory Review 2 A Warm-Up Case 3 Gaussian Discriminate Analysis 4 Naive Bayes 5 Expectation-Maximization (EM) Algorithm Feng Li (SDU) GDA, NB and EM September 27, 2023 2 / 122 Probability P(A � B) = P(A) + P(B) − P(A � B) P(A¬) = 1 − P(A) Feng Li (SDU) GDA, NB and EM September 27, 2023 5 / 122 Conditional Probability Definition of conditional probability: Fraction of worlds in which event

Next 5G Platform David Lenrow Open Source Service Mesh Evangelist Neeraj Poddar Co-founder & Chief Architect, Aspen Mesh February 22, 2021 2 ©2021 Aspen Mesh. All rights reserved. What Is 5G and and Why Does It Matter? 5G wireless technology is meant to deliver higher multi-Gbps peak data speeds, ultra low latency, more reliability, massive network capacity, increased availability, and a more -Qualcomm 3 ©2021 Aspen Mesh. All rights reserved. https://medium.com/5g-nr/5g-service-based-architecture-sba-47900b0ded0a 5G Architecture 4 ©2021 Aspen Mesh. All rights reserved. Key Platform

#IstioCon 5 tips for your first Istio.io Contribution Albert Sun | @albertsun0 #IstioCon About Me I’m a high schooler who loves learning about everything related to computers, especially interface

models achieve higher compression ratio which results in lower transmission and storage costs. Figure 5-1 visually depicts two networks. The one on the left is the original network and the one on the right ourselves that setting parameter values to zero indeed results in a higher compression ratio. Figure 5-1: An illustration of pruning weights (connections) and neurons (nodes) in a neural network consisting scores are assigned, the weights are pruned in the ascending order of their saliency scores. Figure 5-2 describes a sparsity training algorithm. It operates on a pre-trained dense network with weights and

使用适用于 Mac 的 VMware View Client 2012 年 5 月 适用于 Mac 的 View Client 在本文档被更新的版本替代之前，本文档支持列出的每个产 品的版本和所有后续版本。要查看本文档的更新版本，请访 问 http://www.vmware.com/cn/support/pubs。 ZH_CN-000668-03 使用适用于 Mac 的 VMware View com/cn 广州办公室 广州市天河北路 233 号 中信广场 7401 室 www.vmware.com/cn 目录 1 使用适用于 Mac 的 VMware View Client 5 设置和安装 5 Mac 客户端的系统要求 6 支持的 View 桌面操作系统 6 准备适用于 View Client 的 View 连接服务器 6 在 Mac OS X 上安装 View Client 这些信息面向需要设置包含 Mac 客户端设备的 VMware View 部署的管理员。本文档中的信息专门为已熟练掌 握虚拟机技术和数据中心操作、并具有丰富经验的系统管理员编写。 n 设置和安装第 5 页， 设置适用于 Mac 客户端的 View 部署涉及以下内容：使用特定 View 连接服务器配置设置，满足 View 服 务器和 Mac 客户端对系统的要求，以及从 VMware 网站下载并安装适用于

基础：图像分类问题定义与说明 图像分类问题 语义级分类 细粒度分类 图像分类问题 实例级分类 识别问题 图像分类问题 实例级分类 识别问题 图像分类问题 图像分类评估：Top-1 / Top-5 准确率 图像分类评估：混淆矩阵 图像分类评估：ROC 曲线 基础：越来越深的图像分类网络 历年 SOTA 模型对比 AlexNet（2012） AlexNet（2012） AlexNet（2012）

具有多种部署方式的数据库和消息队列软件， 快速发现洞察并采取行动 VMware SQL Postgres & MySQL VMware RabbitMQ® 消息代理 & 日志流 VMware Greenplum® VMware Tanzu Data Science Services 数据仓库 & 大数据平台 分布式内存计算网格 所需而变得的人工智能与数据科学 • 结对编程 • 敏捷交付 VMware On-demand AI with Data Science Application Transformation RabbitMQ® Message Broker & Log Streaming Greenplum® Data Warehouse & Big Data Platform 数字化转型过程中的数据流转 GemFire® In-Memory Data Grid and Cache ETL/CDC Message Broker VMware GemFire In-Memory Data-Grid & Geo-Replication ©2022 VMware, Inc. VMware Greenplum Comprehensive Data Analytics Warehouse VMware Data Services Manager Cloud Native abstraction