lotus-zheng's starred repositories
CS5284_2024
NUS CS5284 Graph Machine Learning course, Xavier Bresson, 2024
fb.resnet.torch
Torch implementation of ResNet from http://arxiv.org/abs/1512.03385 and training scripts
hello-algo
《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新，English version ongoing
kuboard-press
Kuboard 是基于 Kubernetes 的微服务管理界面。同时提供 Kubernetes 免费中文教程，入门教程，最新版本的 Kubernetes v1.23.4 安装手册，(k8s install) 在线答疑，持续更新。
deep-residual-networks
Deep Residual Learning for Image Recognition
llm-course
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
serverless-ml-course
Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features
DeslantImg
The deslanting algorithm sets text upright in images. Python, C++ and OpenCL implementations provided.
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!）
campus_recruitmen_questions
2021年最新整理，5000道秋招/提前批/春招/常用面试题（含答案），包括leetcode，校招笔试题，面试题，算法题，语法题。
script_buddy_v2
Script Buddy v2 is a film script text generation tool built using film scripts from the world's most popular film scripts and GPT2.
CollaborativeFiltering
Implementation of Collabrative Filtering way of recommendation engine
recommendation
实现了基于协同过滤(UserCF)的模型、基于隐语义(LFM)的模型、基于图(PersonalRank)的模型，并结合三种模型的结果给出最终结果的推荐算法
AlphaTree-graphic-deep-neural-network
AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN），图神经网络（GNN），NLP，大数据相关的发展路书(roadmap), 并附海量源码（python，pytorch）带大家消化基本知识点，突破面试，完成从新手到合格工程师的跨越，其中深度学习相关论文附有tensorflow caffe官方源码，应用部分含推荐算法和知识图谱
Recommendation-systems
Recommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems
pyRecommender
基于知识图谱的推荐系统
latex-cookbook
LaTeX论文写作教程 (清华大学出版社)
imbalanced-ensemble
🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库
imbalanced-learn
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
imbalanced-dataset-sampler
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
Forecasting-Weather-Using-Machine-Learning
Forecasting weather Using Multinomial Logistic Regression, Decision Tree, Naïve Bayes Multinomial, and Support Vector Machine