nomoreoneday

awesome-dynamic-pricing

😎 awesome dynamic pricing 💵

learn_python

Python 学习笔记

llm-cookbook

面向开发者的 LLM 入门教程，吴恩达大模型系列课程中文版

llm-action

本项目旨在分享大模型相关技术原理以及实战经验。

awesome-llm-understanding-mechanism

awesome papers in LLM interpretability

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Awesome-GNN4TS

[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)

Awesome-Graph-Causal-Learning

A list of Graph Causal Learning materials.

NeuralCausalModels

Neural Causal Model (NCM) implementation by the authors of The Causal Neural Connection.

notears

DAGs with NO TEARS: Continuous Optimization for Structure Learning

LeetCode-Py

⛽️「算法通关手册」：超详细的「算法与数据结构」基础讲解教程，从零基础开始学习算法知识，850+ 道「LeetCode 题目」详细解析，200 道「大厂面试热门题目」。

awesome-cs-books

🔥 经典编程书籍大全，涵盖：计算机系统与网络、系统架构、算法与数据结构、前端开发、后端开发、移动开发、数据库、测试、项目与团队、程序员职业修炼、求职面试等

Awesome-AIGC-Tutorials

Curated tutorials and resources for Large Language Models, AI Painting, and more.

LearnPrompt

永久免费开源的 AIGC 课程, 目前已支持Prompt Engineering, ChatGPT, Midjourney, Runway, Stable Diffusion, AI数字人，AI声音&音乐，开源大模型

PytorchNetHub

项目注释+论文复现+算法竞赛+Pytorch实践

EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

awesome-machine-learning-1

Learning Resources And Links Of Machine Learning（updating）

TSFpaper

This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.

Generalization-Causality

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

causal-learn

Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

py-causal

CausalInferenceIntro

Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure

deep-ctr-prediction

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

imbalanced-regression

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

Recommender-System-LightFM

scalable Recommeder System for e-commerece using LightFM package in python

Time-Series-Analysis-Tutorial

时间序列分析教程

libpostal

A C library for parsing/normalizing street addresses around the world. Powered by statistical NLP and open geo data.

matrix-factorization

Library for matrix factorization for recommender systems using collaborative filtering

PyTorch-Tutorial

Build your neural network easy and fast, 莫烦Python中文教学