optimus-logger Config [Jenkins] search Jenkins ON-Prem optimus-logger configuration Back to Dashboard Project name optimus-logger Status Description Docker build optimum logger on git changes Branch Specifier (blank for 'any') */master Add Branch Delete Branch ## optimus-logger Config [Jenkins] Git executable Repository browser Default (Auto) ![Image](/uploads/documents/a/a/

# Machine Learning Lecture 10: Neural Networks and Deep Learning Feng Li fli@sdu.edu.cn https://funglee.github.io School of Computer Science and Technology Shandong University Fall 2018 ## Deep Feedforward $ is usually a highly non-linear function • Feedforward networks are of extreme importance to machine learning practitioners - The conventional neural networks (CNN) used for object recognition from

Container Platform 4.14 Operator 在 OpenShift Container Platform 中使用 Operator Last Updated: 2024-02-23 OpenShift Container Platform 4.14 Operator 在 OpenShift Container Platform 中使用 Operator 法律通告 法律通告 Copyright 本文档提供有关在 OpenShift Container Platform 中使用 Operator 的信息。文中为集群管理员提供 了 Operator 的安装和管理说明，为开发人员提供了如何通过所安装的 Operator 创建应用程序的信 息。另外还提供了一些使用 Operator SDK 构建自用 Operator 的指南。 . . . . . . . . . . . . . . . . . 目 目录 录 第 第 1 章 章 OPERATOR 概述 概述 1.1. 对于开发人员 1.2. 对于管理员 1.3. 后续步骤 第 第 2 章 章 了解 了解 OPERATOR 2.1. 什么是 OPERATOR? 2.2. OPERATOR FRAMEWORK 打包格式 2.3. OPERATOR FRAMEWORK 常用术语表 2.4. OPERATOR LIFECYCLE MANAGER

## Machine Learning Pytorch Tutorial TA：曾元(Yuan Tseng) 2022.02.18 ## Outline Background: Prerequisites & What is Pytorch? • Training & Testing Neural Networks in Pytorch • Dataset & Dataloader [Image](/uploads/documents/7/6/e/1/76e1a67e96719ae74c41b110fe07bfe6/p3_2.jpg) ## What is PyTorch? - An machine learning framework in Python. • Two main features: ○ N-dimensional Tensor computation (like NumPy) synthesis, ...) ☐ Most implementations of recent deep learning papers ○ ... ## References • Machine Learning 2021 Spring Pytorch Tutorial • Official Pytorch Tutorials https://numpy.org/ Any questions

## Debugging the BPF Virtual Machine eBPF Summit ## Why? ● Debugging is useful to understand how things work ● Sometimes, eBPF programs can’t even load - I couldn’t find good resources on this, so so, here I am ● I break lots of eBPF programs - The BPF Virtual machine is not easy to understand ## The approach ## The BPF subsystem lives in the kernel ![Image](/uploads/documents/7/1/6/1/7161fc3

Back to Basics: The Abstract Machine Bob Steagall CppCon 2020 ## KEWB COMPUTING ## Overview/Goals • Describe abstract machines in general • Describe the C++ abstract machine specifically • Language goals • Important components of the abstract machine, and their relationships • Provide a useful overview of the C++ abstract machine ## What is an Abstract Machine? “Abstract machines are machines because between the high level of a programming language and the low level of a real machine. The instructions of an abstract machine are tailored to the particular operations required to implement operations of

1. OPENSHIFT CONTAINER PLATFORM 安装概述 ..... 14 3.2. 关于 OPENSHIFT UPDATE 服务 ..... 19 3.3. 非受管 OPERATOR 的支持策略 ..... 20 3.4. 后续步骤 ..... 20 第4章 RED HAT OPENSHIFT CLUSTER MANAGER ..... 22 4.1. 访问 RED CONTAINER PLATFORM 中的机器角色 ..... 26 5.3. OPENSHIFT CONTAINER PLATFORM 中的 OPERATOR ..... 29 5.4. 关于 MACHINE CONFIG OPERATOR ..... 30 第6章 了解 OPENSHIFT CONTAINER PLATFORM 开发 ..... 33 6.1. 关于容器化应用程序开发 6.2. 构建一个简单容器 ..... 33 6.3. 为 OPENSHIFT CONTAINER PLATFORM 创建 KUBERNETES 清单 ..... 36 6.4. 面向 OPERATOR 进行开发 ..... 38 第7章 RED HAT ENTERPRISE LIUX COREOS (RHCOS) ..... 39 7.1. 关于 RHCOS ..... 39 7

## Kubernetes Operator 实践 —— MySQL 容器化 刘林 搜狗资深工程师 ## 关于我  刘林 ## 搜狗商业平台研发部资深开发工程师 - 主要从事商业平台研发工作，在构建高性能、高可用大规模系统方面有丰富的实践经验 践经验 - 目前专注于云计算、DevOps 等相关领域，负责搜狗商业云平台的设计研发工作 ## TABLE OF CONTENTS 大纲 1. 背景介绍 2. Operator 的基本原理 3. MySQL Operator 设计实践 4. 小结 ## 搜狗商业平台  elasticsearch ## 有状态服务容器化 ## TABLE OF CONTENTS 大纲 1. 背景介绍 2. Operator 的基本原理 3. MySQL Operator 设计实践 4. 小结 ## 带来的新挑战 无状态服务 有状态服务 服务调度 ↓ 服务调度 状态保存 有状态服务集群 服务调度 状态保存 集群管理

# Lecture Notes on Support Vector Machine Feng Li fli@sdu.edu.cn Shandong University, China ## 1 Hyperplane and Margin In a n-dimensional space, a hyper plane is defined by $$ \omega^{T}x+b=0 $$ 7b9d33d07aa393893fb3862bcd67/p2_1.jpg) Figure 1: Margin and hyperplane. ## 2 Support Vector Machine ### 2.1 Formulation The hyperplane actually serves as a decision boundary to differentiating positive we can construct a infinite number of hyperplanes, but which one is the best? Supported Vector Machine (SVM) answers the above question by maximizing $ \gamma $ (see Eq. (6)) as follows $$ \begin

## Lecture 6: Support Vector Machine Feng Li Shandong University fli@sdu.edu.cn December 28, 2021 ## Outline  1 SVM: moving it parallelly along $ \omega $ (b < 0 means in opposite direction) ## Support Vector Machine • A hyperplane based linear classifier defined by $ \omega $ and b • Prediction rule: $ y = [Image](/uploads/documents/4/1/3/0/41305aec36322a1beae76d1d88486b9a/p14_2.jpg) ## Support Vector Machine (Primal Form) • Maximizing $ 1/\|\omega\| $ is equivalent to minimizing $ \|\omega\|^{2}=\omega^{T}\omega