电子科技大学：《遥感地面数据采集与实验方法 Methods for Remote Sensing Experiment》课程教学资源（教学大纲，周纪）

电子科技大学：《遥感地面数据采集与实验方法 Methods for Remote Sensing Experiment》课程教学资源（课件讲稿）实验02 地物反射光谱采集实验

电子科技大学：《遥感地面数据采集与实验方法 Methods for Remote Sensing Experiment》课程教学资源（课件讲稿）实验04 气象参数采集实验

5.1 数组的类型定义 5.2 数组的顺序表示和实现 5.3 稀疏矩阵的压缩存储 5.4 广义表的类型定义 5.5 广义表的表示方法 5.6 广义表操作的递归函数

• 11.1图计算简介 • 11.2Pregel简介 • 11.3Pregel图计算模型 • 11.4Pregel的C++ API • 11.5Pregel的体系结构 • 11.6Pregel的应用实例 • 11.7 Pregel和MapReduce实现PageRank算法的对比 • 11.8 Hama的安装和使用

◼ Why Data Mining? ◼ What Is Data Mining? ◼ A Multi-Dimensional View of Data Mining ◼ What Kinds of Data Can Be Mined? ◼ What Kinds of Patterns Can Be Mined? ◼ What Kinds of Technologies Are Used? ◼ What Kinds of Applications Are Targeted? ◼ Major Issues in Data Mining ◼ A Brief History of Data Mining and Data Mining Society ◼ Summary

《经济数据分析 Analysis of Economic Data》课程教学资源（PPT课件讲稿，英文版）Lesson 11 Regressions Part II

1 Introduction Problem Definition Existing Methods Motivation and Contribution 2 Isotropic Hashing Model Learning Experimental Results 3 Multiple-Bit Quantization Double-Bit Quantization Manhattan Quantization 4 Conclusion 5 Reference

1 Introduction 2 Unsupervised Hashing 3 Supervised Hashing 4 Ranking-based Hashing 5 Multimodal Hashing 6 Deep Hashing 7 Quantization 8 Conclusion 9 Reference

《人工智能、机器学习与大数据》课程教学资源（参考文献）Buffered Asynchronous SGD for Byzantine Learning