Course-Recommendation-SystemA system that will help in a personalized recommendation of courses for an upcoming semester based on the performance of previous semesters.
Stars: ✭ 14 (-98.98%)
GNN-Recommender-SystemsAn index of recommendation algorithms that are based on Graph Neural Networks.
Stars: ✭ 505 (-63.06%)
recsys2019The complete code and notebooks used for the ACM Recommender Systems Challenge 2019
Stars: ✭ 26 (-98.1%)
EasyRecA framework for large scale recommendation algorithms.
Stars: ✭ 599 (-56.18%)
recommenderNReco Recommender is a .NET port of Apache Mahout CF java engine (standalone, non-Hadoop version)
Stars: ✭ 35 (-97.44%)
MARankMulti-order Attentive Ranking Model for Sequential Recommendation
Stars: ✭ 25 (-98.17%)
YueA python library for music recommendation
Stars: ✭ 88 (-93.56%)
BPR MPRBPR, Bayesian Personalized Ranking (BPR), extremely convenient BPR & Multiple Pairwise Ranking
Stars: ✭ 77 (-94.37%)
Causal Reading GroupWe will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.
Stars: ✭ 339 (-75.2%)
online-course-recommendation-systemBuilt on data from Pluralsight's course API fetched results. Works with model trained with K-means unsupervised clustering algorithm.
Stars: ✭ 31 (-97.73%)
epi😬 Hours upon hours upon hours of awful interview prep
Stars: ✭ 16 (-98.83%)
front-end-interview-guide前端面试手册,含JS,HTML,CSS,算法和数据结构,计算机系统,计算机网络,浏览器,性能优化,前端工程化,数据库,前端框架,小程序,设计模式,数据可视化
Stars: ✭ 42 (-96.93%)
Coding-Interview-ChallengesThis is a repo where I upload code for important interview questions written in Python, C++, and Swift
Stars: ✭ 13 (-99.05%)
studyNotesLearning the various documents and small projects
Stars: ✭ 46 (-96.63%)
EATNNThis is our implementation of EATNN: Efficient Adaptive Transfer Neural Network (SIGIR 2019)
Stars: ✭ 23 (-98.32%)
Java-Rule-BookBasic concepts of Java to answer any question about how Java works
Stars: ✭ 36 (-97.37%)
STACPJoint Geographical and Temporal Modeling based on Matrix Factorization for Point-of-Interest Recommendation - ECIR 2020
Stars: ✭ 19 (-98.61%)
MoHRMoHR: Recommendation Through Mixtures of Heterogeneous Item Relationships
Stars: ✭ 51 (-96.27%)
KG4RecKnowledge-aware recommendation papers.
Stars: ✭ 76 (-94.44%)
BARSTowards open benchmarking for recommender systems https://openbenchmark.github.io/BARS
Stars: ✭ 157 (-88.51%)
learning-computer-scienceLearning data structures, algorithms, machine learning and various computer science constructs by programming practice from resources around the web.
Stars: ✭ 28 (-97.95%)
skywalkRcode for Gogleva et al manuscript
Stars: ✭ 28 (-97.95%)
TIFUKNNkNN-based next-basket recommendation
Stars: ✭ 38 (-97.22%)
LeetCode✍️ My LeetCode solutions, ideas and templates sharing. (我的LeetCode题解,思路以及各专题的解题模板分享。分专题归纳,见tag)
Stars: ✭ 123 (-91%)
PythonRepository for Python codes and algos. Star the repo too.
Stars: ✭ 102 (-92.54%)
CodingInterviewSolutions to Leetcode, CareerCup Coding problems
Stars: ✭ 64 (-95.32%)
hackfastalgosA library of various fast algorithms written in Hack
Stars: ✭ 34 (-97.51%)
Graph-AlgorithmsEverything you need to know about graph theory to ace a technical interview 🔥
Stars: ✭ 87 (-93.64%)
Coding-Interview-101Solutions to LeetCode problems filtered with companies, topics and difficulty.
Stars: ✭ 21 (-98.46%)
interview questionsRecruitment questions I (or colleagues ;)) heard/were asked during interviews. Good for a learning purpose.
Stars: ✭ 33 (-97.59%)
Auto-SurpriseAn AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀
Stars: ✭ 19 (-98.61%)
Backend-NodeJS-Golang-Interview QAA collection of Node JS and Golang Backend interview questions please feel free to fork and contribute to this repository
Stars: ✭ 122 (-91.08%)
LeetCode🎆LeetCode solution and explanation
Stars: ✭ 54 (-96.05%)
iOS-Interview📚 Comprehensive list of questions and problems to pass an interview for the iOS Developer position
Stars: ✭ 127 (-90.71%)
JavaScript-ResourcesCurated list of 10 resources to ace your next JavaScript interview
Stars: ✭ 39 (-97.15%)
websight🕷A simple but *really* fast crawler built with Node.js & TypeScript
Stars: ✭ 15 (-98.9%)
chainRecMengting Wan, Julian McAuley, "Item Recommendation on Monotonic Behavior Chains", in Proc. of 2018 ACM Conference on Recommender Systems (RecSys'18), Vancouver, Canada, Oct. 2018.
Stars: ✭ 52 (-96.2%)
NeuralCitationNetworkNeural Citation Network for Context-Aware Citation Recommendation (SIGIR 2017)
Stars: ✭ 24 (-98.24%)
rec-a-sketchcontent discovery... IN 3D
Stars: ✭ 45 (-96.71%)
code interviewLeetCode LintCode 题解, 剑指offer题目,互联网公司面试,BAT外企等面试题目
Stars: ✭ 21 (-98.46%)
bprBayesian Personalized Ranking using PyTorch
Stars: ✭ 105 (-92.32%)
Algorithm-ImplementationsLots of algorithm's & their implementations that have been compiled from a variety of locations.
Stars: ✭ 15 (-98.9%)
adversarial-recommender-systems-surveyThe goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…
Stars: ✭ 110 (-91.95%)