Stars
基于大模型搭建的聊天机器人，同时支持 微信公众号、企业微信应用、飞书、钉钉 等接入，可选择GPT3.5/GPT-4o/GPT-o1/ Claude/文心一言/讯飞星火/通义千问/ Gemini/GLM-4/Claude/Kimi/LinkAI，能处理文本、语音和图片，访问操作系统和互联网，支持基于自有知识库进行定制企业智能客服。
中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)
2022 Recommendation System Related Top Conference Papers
Paper List for Recommend-system PreTrained Models
This repository collects recent top papers about knowledge-aware recommendations. We will keep updating the paper list weekly.
This is the framework with 17 existing crowdsourced truth inference algorithms.
Semantic Structure-based Unsupervised Deep Hashing IJCAI2018
The original implementation of the models and experiments of Variational Deep Semantic Hashing paper (SIGIR 2017)
source code for paper "Refining BERT Embeddings for Document Hashing via Mutual Information Maximization"
A curated list of resources for Learning with Noisy Labels
A comprehensive list of Awesome Contrastive Learning Papers&Codes.Research include, but are not limited to: CV, NLP, Audio, Video, Multimodal, Graph, Language, etc.
Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)
Bandit algorithms for online learning to rank
“Chorus” of recommendation models: a light and flexible PyTorch framework for Top-K recommendation.
Code to reproduce experiments from the ACL 2016 paper about Rumour Stance Classification with Hawkes Processes.
Code for Transformer Hawkes Process, ICML 2020.
LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)
Hawkes Intensity Process Implemented in TensorFlow
Python class for generation and parameter estimation of multivariate Hawkes processes
TensorFlow Implementation of Neural Attentive Item Similarity Model for Recommendation on TKDE 2018
WWW'2019: Modeling Item-Specific Temporal Dynamics of Repeat Consumption for Recommender Systems
CLV prediction with pareto-NBD model
We will use python to replicate the BG-NBD (Beta Geometric Negative Binomial Distribution) model that is described in the paper “Counting Your Customers” the Easy Way: An Alternative to the Pareto/…
This is a group project for E-commerce repeat buyers purchase prediction using machine learning while accounting for imbalance outcome for consulting purposes
Predicting Consumption Patterns with Repeatedand Novel Events
A curated list of network embedding techniques.
A collection of implementations of deep domain adaptation algorithms