pipipiu Goto Github PK

3y

:notebook:从Java基础、JavaWeb基础到常用的框架再到面试题都有完整的教程，几乎涵盖了Java后端必备的知识点

adabelief-optimizer

Repository for NeurIPS 2020 Spotlight "AdaBelief Optimizer: Adapting stepsizes by the belief in observed gradients"

adversarial-recsys

📕 Adversarial Attacks and Defenses for Image-Based Recommendation Systems using Deep Neural Networks.

aip

Adversarial Item Promotion in visually-aware recommenders

apl

Tensorflow implementation of Adversarial Pairwise Learning (APL)

apollo

An open autonomous driving platform

applied_machine_learning_apache_spark

Apache® Spark™ for Machine Learning and Data Science

awescnb-g

🎉 快速切换多套博客园主题皮肤

awesome-material

awesome material

bank_interview

:bank: 银行笔试面试经验分享及资料分享（help you pass the bank interview, and get a amazing bank offer!）

bbcnewsdatamining

benchmarking-gnns

Repository for benchmarking graph neural networks

bigdata-notes

大数据入门指南 :star:

binary

Sleep_Pwn_f1sh

build-your-own-meanshift

How to Build Your Own Meanshift in Python

butian_spider

2019 补天厂商爬虫与数据可视化文件打包

bzpro

BZOJ离线题库 附赠爬虫一枚

c_o_d_5th

计算机组成与设计 硬件/软件接口 第5版 ; Patterson, Hennessy: Computer Organization and Design:The Hardware/Software Interface,5th Edition.

course

整理社团历次宣讲会的课件及文章推荐

cs-interview-knowledge-map

Build the best interview map. The current content includes JS, network, browser related, performance optimization, security, framework, Git, data structure, algorithm, etc.

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

csapp-3e-solutions

CSAPP 3e Solutions gitbook

ctf-tools

这里存放的是我们团队做CTF题目的时候经常用到的一些工具

ctr_prediction

CTR prediction using FM FFM and DeepFM

cvm

Python implementation of the algorithms in the book Computer Vision: Models, Learning and Inference

data-competition-topsolution

Data competition Top Solution 数据竞赛top解决方案开源整理

data_science_fundamentals

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

deeprobust

A pytorch adversarial library for attack and defense methods on images and graphs

dive-into-dl-pytorch

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。