私立华联学院：《英语精读》课程PPT教学课件（A New English Course）Unit 4 Network Desinger——-Tim Berners-Lee

Uncertainty Probability Syntax and Semantics Inference Independence and Bayes’ Rule Bayesian network Graphical models Bayesian networks Inference in Bayesian networks

清华大学：Computational Models for Social Network Analysis（PPT讲稿）mining big social networks（Part III：Group and Structure）

同济大学：《大学计算机基础》课程教学资源（教案讲义）Fundamentals of Network 2

FairCloud：Sharing the Network in Cloud Computing

▪ Perceptron Introduction ▪ Deep Neural Network Structure ▪ Backpropagation

 MAC (Medium Access Control)  Ethernet  CSMA/CD  Backoff Algorithm  Frame Structure  Experiences with Ethernet  Bridges and LAN switches  Reading list

• Introduction • Supervised Learning – Convolutional Neural Network – Sequence Modelling: RNN and its extensions • Unsupervised Learning – Autoencoder – Stacked DenoisingAutoencoder • Reinforcement Learning – Deep Reinforcement Learning – Two applications: Playing Atari & AlphaGo

1 I/O Hardware and I/O control methods Polling (轮询方式) Interrupts (中断方式) Direct Memory Access (DMA方式) I/O hardware summary 2 Application I/O Interface Block and Character Devices Network Devices Clocks and Timers Blocking (阻塞) and Nonblocking (非阻塞) I/O 3 Kernel I/O Subsystem I/O Scheduling Buffering (缓冲机制) Caching, Spooling & device reservation Error Handling I/O Protection Kernel Data Structures 4 Transforming I/O Requests to Hardware Operations 5 Performance

1、引例 2、贝叶斯概率基础 3、贝叶斯网络概述 4、贝叶斯网络的预测、诊断和训练 4.1 贝叶斯网络的预测 4.2 贝叶斯网络的诊断 4.3 贝叶斯网络的训练