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此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
Interview Questions for Google, Amazon, Apple, etc. 根据超过 2000 篇真实面经整理的腾讯,阿里,字节跳动,Shopee,美团,滴滴高频面试题
计算机基础(计算机网络/操作系统/数据库/Git...)面试问题全面总结,包含详细的follow-up question以及答案;全部采用【问题+追问+答案】的形式,即拿即用,直击互联网大厂面试;可用于模拟面试、面试前复习、短期内快速备战面试...
A collection of full time roles in SWE, Quant, and PM for new grads.
Cracking the Coding Interview 6th Ed. Solutions
『Java八股文』Java面试套路,Java进阶学习,打破内卷拿大厂Offer,升职加薪!
LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解,记录自己的leetcode解题之路。)
《代码随想录》LeetCode 刷题攻略:200道经典题目刷题顺序,共60w字的详细图解,视频难点剖析,50余张思维导图,支持C++,Java,Python,Go,JavaScript等多语言版本,从此算法学习不再迷茫!🔥🔥 来看看,你会发现相见恨晚!🚀
A latent text-to-image diffusion model
High-Resolution Image Synthesis with Latent Diffusion Models
Solutions to Python for Everybody: Exploring Data using Python 3 by Charles Severance
Refine high-quality datasets and visual AI models
This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
阴阳师后台代肝脚本,支持所有类似阴阳师的卡牌游戏(点点点游戏)自动找图-点击…(支持后台运行、支持多开、支持模拟器)
[NeurIPS 2022] Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach -- Official Implementation
Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)
Recommendation Algorithm大规模推荐算法库,包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM,DSIN,SIGN,IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESM…
[ICDE 2022]Cross-Domain Recommendation to Cold-Start Users via Variational Information Bottleneck
Implementation of "Reinforcement Learning-enhanced Shared-account Cross-domain Sequential Recommendation" (TKDE 2022)