Lecture 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 1600

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 Android

SAP 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 Practices series

APACHE 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Experiment 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 who

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

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 Docker

Chapter 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 When

Oracle R ⃝ VM VirtualBox R ⃝ User Manual Version 7.0.0_BETA2 Copyright c⃝ 2004-2022 Oracle and/or its affiliates http://www.virtualbox.org Contents Preface i 1 First Steps 1 1.1 Why is Virtualization . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Some Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Features Overview . . . . . . . . . . . . . . . . . . 37 1.19 Configuration Details and Runtime Information of Virtual Machines . . . . . . . 37 2 Contents 1.19.1 Virtual Machine Details Widget . . . . . . . . . . . . . . . . . . . . . . 37 1.19

Oracle R ⃝ VM VirtualBox R ⃝ User Manual Version 6.0.0_BETA2 c⃝ 2004-2018 Oracle Corporation https://www.virtualbox.org Contents 1 First Steps 12 1.1 Why is Virtualization Useful? . . . . . . . 34 1.17 Alternative Front-Ends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 2 Installation Details 36 2.1 Installing on Windows Hosts . . . . . . . . . . . . . . . . . . . . . . . . 44 2.4.1 Performing the Installation . . . . . . . . . . . . . . . . . . . . . . . . . 44 2 Contents 2.4.2 The vboxuser Group . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 2