Cloud Native Contrail Networking
Installation and Life Cycle ManagementGuide for Rancher RKE2Cloud Native Contrail Networking Installation and Life Cycle Management Guide for Rancher RKE2 Published 2023-09-08 Juniper Networks, Inc. 1133 Innovation Way Sunnyvale, California 94089 USA 408-745-2000 notice. Cloud Native Contrail Networking Installation and Life Cycle Management Guide for Rancher RKE2 Copyright © 2023 Juniper Networks, Inc. All rights reserved. The information in this document is Networking Overview | 2 Terminology | 4 CN2 Components | 6 Deployment Models | 11 Single Cluster Deployment | 11 Multi-Cluster Deployment | 12 System Requirements | 15 2 Install Overview0 码力 | 72 页 | 1.01 MB | 1 年前3
SUSE Rancher and RKE Kubernetes cluster
using CSI Driver on DELL EMC PowerFlexSUSE Rancher and RKE Kubernetes cluster using CSI Driver on DELL EMC PowerFlex September 2021 H18899 White Paper Abstract This white paper describes the deployment of a SUSE Rancher Kubernetes Technologies Solutions PowerFlex Engineering Validated Copyright 2 SUSE Rancher and RKE Kubernetes cluster using CSI Driver on DELL EMC PowerFlex White Paper The information The information is subject to change without notice. Contents 3 SUSE Rancher and RKE Kubernetes cluster using CSI Driver on DELL EMC PowerFlex White Paper Contents Executive0 码力 | 45 页 | 3.07 MB | 1 年前3
Lecture 2: Linear RegressionLecture 2: Linear Regression Feng Li Shandong University fli@sdu.edu.cn September 13, 2023 Feng Li (SDU) Linear Regression September 13, 2023 1 / 31 Lecture 2: Linear Regression 1 Supervised Learning: Learning: Regression and Classification 2 Linear Regression 3 Gradient Descent Algorithm 4 Stochastic Gradient Descent 5 Revisiting Least Square 6 A Probabilistic Interpretation to Linear Regression Regression September 13, 2023 2 / 31 Supervised Learning Regression: Predict a continuous value Classification: Predict a discrete value, the class Living area (feet2) Price (1000$s) 2104 400 16000 码力 | 31 页 | 608.38 KB | 1 年前3
《TensorFlow 2项目进阶实战》7-TensorFlow2进阶使用TensorFlow 2 进阶使用 扫码试看/订阅 《 TensorFlow 2项目进阶实战》视频课程 • 使⽤ TensorFlow 2 实现图像数据增强 • 使⽤ TensorFlow 2 实现分布式训练 • 使⽤ TensorFlow Hub 迁移学习 • 使⽤ @tf.function 提升性能 • 使⽤ TensorFlow Serving 部署云端服务 • 使⽤ TensorFlow TensorFlow Lite 实现边缘智能 目录 使⽤ TensorFlow 2 实现图像数据增强 使⽤ TensorFlow 2 实现分布式训练 使⽤ TensorFlow Hub 迁移学习 7 8 9 11 12 13 使⽤ @tf.function 提升性能 使⽤ TensorFlow Serving 部署云端服务 使⽤ TensorFlow Lite 实现边缘智能 TensorFlow clone https://github.com/tensorflow/examples Step 2:在 Android Studio 中加载 examples 项目 项目路径:examples/lite/examples/image_classification/android Step 2:在 Android Studio 中加载 examples 项目 Step 3:在 Android0 码力 | 28 页 | 5.84 MB | 1 年前3
Rancher Kubernetes Engine 2, VMWare vSANSAP Data Intelligence 3 on Rancher Kubernetes Engine 2 using VMware vSAN and vSphere SUSE Linux Enterprise Server 15 SP4 Rancher Kubernetes Engine 2 SAP Data Intelligence 3 Dr. Ulrich Schairer, SAP Solutions 1 SAP Data Intelligence 3 on Rancher Kubernetes Engine 2 using VMware vSAN and vSphere SAP Data Intelligence 3 on Rancher Kubernetes Engine 2 using VMware vSAN and vSphere Date: 2023-07-24 SAP Data document describes the installation and configuration of SAP Data Intelligence 3 deployed on SUSE's RKE2 and VMWare vsphere and vsan. Disclaimer: Documents published as part of the SUSE Best Practices0 码力 | 29 页 | 213.09 KB | 1 年前3
Apache Karaf Decanter 2.x - DocumentationAPACHE KARAF DECANTER 2.X - DOCUMENTATION Apache Software Foundation APACHE KARAF DECANTER 2.X - DOCUMENTATION 1. User Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2.2. CXF Logging feature integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2.3. Log Socket . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 2. Developer Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .0 码力 | 64 页 | 812.01 KB | 1 年前3
Experiment 2: Logistic Regression and Newton's MethodExperiment 2: Logistic Regression and Newton’s Method August 29, 2018 1 Description In this exercise, you will use Newton’s Method to implement logistic regression on a classification problem. 2 Data To To begin, download data2.zip and extract the files from the zip file. For this exer- cise, suppose that a high school has a dataset representing 40 students who were admitted to college and 40 students first column of your x array represents all Test 1 scores, and the second column represents all Test 2 scores, and the y vector uses “1” to label a student who was admitted and “0” to label a student who0 码力 | 4 页 | 196.41 KB | 1 年前3
《TensorFlow 2项目进阶实战》1-基础理论篇:TensorFlow 2设计思想TensorFlow 2 项目实战进阶 扫码试看/订阅 《TensorFlow 2 项目进阶实战》视频课程 基础理论篇:TensorFlow 2 设计思想 • TensorFlow 2 设计原则 • TensorFlow 2 核心模块 • TensorFlow 2 vs TensorFlow 1.x • TensorFlow 2 落地应用 目录 TensorFlow 2 设计原则 TensorFlow of AI TensorFlow 2 设计原则 TensorFlow 2 简化概念 海纳百川 构建生态 TensorFlow 2 简化概念 1.0 2.0 TensorFlow 2 海纳百川 2.0 TensorFlow 2 构建生态 2.0 TensorFlow 生产级AI方案 TensorFlow 2 核心模块 TensorFlow 2 核心模块概览 tf.keras:分布式和高性能的 模型格式 TensorFlow 2 vs TensorFlow 1.x Keras vs TensorFlow 1.x TensorFlow 1.x 工作流 Full of abstract notions TensorFlow 2 工作流 Native Friendly to TensorFlow 生产级 AI 方案 TensorFlow 2 落地应用 TensorFlow 与移动互联网的结合0 码力 | 40 页 | 9.01 MB | 1 年前3
《TensorFlow 2项目进阶实战》2-快速上手篇:动⼿训练模型和部署服务TensorFlow 2 项目实战进阶 扫码试看/订阅 《TensorFlow 2 项目进阶实战》视频课程 快速上手篇:动⼿训练模型和部署服务 • TensorFlow 2 开发环境搭建 • 使用 tf.keras.datasets 加载数据 • 使用 tf.data.Dataset 加载数据 • 使用 tf.keras.Model 管理模型 • Fashion MNIST 数据集介绍 数据集介绍 • 使用 TensorFlow 2 训练分类网络 目录 TensorFlow 2 开发环境搭建 TensorFlow 2 支持的操作系统 • Python 3.5–3.7 • Ubuntu 16.04 or later • Windows 7 or later • macOS 10.12.6 (Sierra) or later (no GPU support) • Raspbian TensorFlow 2 在 Jupyter Lab 中使用 TensorFlow 2 在 Jupyter Lab 中使用 TensorFlow 2 在 Jupyter Lab 中使用 TensorFlow 2 Docker 容器 与 虚拟机 虚拟机 Docker 容器 在 Docker 中使用 TensorFlow 2 在 Docker 中使用 TensorFlow 2 在 Docker0 码力 | 52 页 | 7.99 MB | 1 年前3
《Efficient Deep Learning Book》[EDL] Chapter 2 - Compression TechniquesChapter 2 - Compression Techniques “I have made this longer than usual because I have not had time to make it shorter.” Blaise Pascal In the last chapter, we discussed a few ideas to improve the deep less frequent symbols are assigned longer codes. This is achieved with a simple Huffman Tree (figure 2-1 bottom). Each leaf node in the tree is a symbol, and the path to that symbol is the bit-string assigned the same number of bits. The lookup table (figure 2-1 middle) that contains the symbol-code mapping is transmitted along with the encoded data. Figure 2-1: Huffman Encoding & Huffman Tree. Source When0 码力 | 33 页 | 1.96 MB | 1 年前3
共 748 条
- 1
- 2
- 3
- 4
- 5
- 6
- 75
相关搜索词
CloudNativeContrailNetworkingInstallationandLifeCycleManagementGuideforRancherRKE2SUSERKEKubernetesclusterusingCSIDriveronDELLEMCPowerFlexLectureLinearRegressionTensorFlow快速入门实战TensorFlow2进阶使用EngineVMWarevSANApacheKarafDecanterDocumentationExperimentLogisticNewtonMethod基础理论基础理论设计思想上手训练模型部署服务EfficientDeepLearningBookEDLChapterCompressionTechniques













