链接, 提取码: BlZa
链接, 提取码: BlZa
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汇报1:Google GFS
汇报2:HDFS
汇报3:NoSQL: IBM, Oracle, Memcached
汇报4:BigTable: Bigtable: A Distributed Storage System for Structured Data
汇报5:Survey of Distributed File System Design Choices, Ceph
汇报6:RAID
汇报7:文件IO API
汇报8:ZeroCopy: Efficient data transfer through zero copy;
Design and Implementation of Zero-Copy for Linux
汇报9:MapReduce:simplified data processing on large clusters, 实验
汇报10:完美Hash
汇报11:线性时间排序: 主材料, 备用材料
- 深度大数据技术
学习资源:机器学习技术,课程,Introduction to Machine Learning
汇报12:ML for Big Data
学习资源:深度学习概述论文,CS231n深度学习课程, 深度学习简介,Transfer Learning,GAN PPT,GAN介绍,运行环境安装
汇报13:Deep residual learning for image recognition, Encoder-decoder with atrous separable convolution for semantic image segmentation
汇报14:A Comprehensive Survey on Transfer Learning
汇报15:Generative Adversarial Networks
学习资源:深度大模型开源项目,Diffusion Models
汇报16:Transformer, Attention Is All You Need
汇报17:BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
汇报18:ViT
汇报19:Diffusion Models Beat GANs on Image Synthesis, Diffusion Models: A Comprehensive Survey of Methods and Applications
汇报20:开端:Improving Language Understanding by Generative Pre-Training
汇报21:演化(问答系统):LaMDA: Language Models for Dialog Applications, WebGPT: Browser-assisted question-answering with human feedback, Improving alignment of dialogue agents via targeted human judgements, Improving Language Models by Retrieving from Trillions of Tokens
汇报22:现状:Scaling Language Models: Methods, Analysis & Insights from Training Gophe, PaLM: Scaling Language Modeling with Pathways
学习资源:视觉大模型课程
汇报23:开端:Swin Transformer, MAE
汇报24:现状:DINO, SAM
汇报25:通用模型架构:商汤INTERN, 百度文心UFO 2.0, 华为盘古CV大模型
汇报26:开端:CLIP, Glip, Lseg
汇报27:通用多模态大模型架构:ALBEF, VLMO, BLIP, CoCa, BeiTv3
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大数据基础
大数据分析理论与实践(2023)
lyx: http://www.lyx.org |