这是谷歌三大论文之一的 MapReduce: Simplified Data Processing on Large Clusters 英文原文。我的翻译可以见https://blog.csdn.net/m0_37809890/article/details/87830686

GOPRO_Large：模糊和清晰的图像对;可用于图像修复、去模糊等； 8.9G 云盘链接分享，如有需要，请放心下载；

A Relational Model of Data for Large Shared Data Banks - Edgar Codd, 1970, CACM. Classical work of Edgar Codd, inventor of Relational database theory. Describes how relational model helps to divide large databases on shards, pieces of datasets.

Going_Native__Using_a_Large-Scale_Analysis_of_Android_Apps_to_Create_a_Practical_Native-Code_Sandboxing_Policy 网络安全 安全管理 APT 移动安全 安全对抗

matlab代码gca Interference-Coordination-in-Full-Duplex-HetNet-with-Large-Scale-Antenna-Arrays Paper about Small Cell, Massive MIMO and Full-duplex Introduction 这篇论文研究的是结合了Small Cell, Massive MIMO和Full-duplex这三种5G关键技术的二层异构网络场景，为了消除干扰使得网络总吞吐量达到最大，提出了三种算法。 遗传算法 贪心算法 基于代价的分布式染色算法 前两种均是中心化算法，第三种分布式算法是本文的核心内容。 Matlab Code channel.m : 建立瑞利衰落信道 scene.m : 建立异构网络场景，基站和用户分布 parameter.m : 优化问题的关键参数 dl_capacity.m : 计算网络总吞吐量的函数 normal.m : 矩阵归一化函数 Genetic_Algorithm: 遗传算法模块 Greedy.m : 贪心算法模块 GCA.m : 分布式染色算法模块 mai

Large-Scale C++ Software Design【中文版】 很清晰的电子书

Data processing, implementing related algorithms, tuning, scaling up and finally deploying are some crucial steps in the process of optimising any application. Spark is capable of handling large-scale batch and streaming data to figure out when to cache data in memory and processing them up to 100 times faster than Hadoop-based MapReduce.This means predictive analytics can be applied to streaming and batch to develop complete machine learning (ML) applications a lot quicker, making Spark an ideal candidate for large data-intensive applications. This book focuses on design engineering and scalable solutions using ML with Spark. First, you will learn how to install Spark with all new features from the latest Spark 2.0 release. Moving on, you’ll explore important concepts such as advanced feature engineering with RDD and Datasets. After studying developing and deploying applications, you will see how to use external libraries with Spark.

Haskell in the Large.pdf

bert-large-uncased-pytorch_model.bin 这是1024位的，资源过大，超过一个g，我放百度云上了 768位的看我的博客免费获取

提出了基于”迁移学习+少数磁盘故障预测”的TLDFP模型。 主要采用了TrAdaBoost（权重调整的迁移学习方法)的思想。 作者 张霁 华中科技大学博士 可免费下载。