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Python - 100天从新手到大师
21 Lessons, Get Started Building with Generative AI
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
LLM-powered multiagent persona simulation for imagination enhancement and business insights.
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。
Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method
TensorFlow Tutorial for Time Series Prediction
数学建模和机器学习/深度学习/大模型的笔记和资料（持续更新中......）。
Simple python example on how to use ARIMA models to analyze and predict time series.
A project to deploy an online app that predicts the win probability for each NBA game every day. Demonstrates end-to-end Machine Learning deployment.
Power systems optimization course materials
武汉理工大学2020数学建模国赛国二/美赛国二/数维杯国一/亚太国二/校内集训/优秀论文等资料
Lagrangian Relaxation approach solve QIP
Access data, statistics, and visualizations for New York's electricity grid.
Two examples for distribution network planning (DNP) method based on Second-Order cone programming (SOCP) relaxation and Linear Distflow are included here. The Objective is to minimize the investme…
This repo holds the implementation the paper 'Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM', by Yanhui Liang, Yu Lin, and Qin Lu.
Author: Feras Al-Basha; Research Director: Yossiri Adulyasak; Research Director: Laurent Charlin; MSc in Global Supply Chain Management - Mémoire/Thesis; HEC Montréal.
This set of codes implements our TPWRS paper "Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment". This work is under the open license: CC BY 4.0.
This project utilizes convex optimization for optimal dispatch of power systems using convex DistFlow equations and cvxpy.
Energy trading using DQN
Code for "Accurate Differential Operators for Hybrid Neural Fields", accepted at CVPR 2025
Traffic Forecasting using Graph Convolution + LSTM model is a ML model developed during the learning process of GCN. The primary soorce of this project is https://github.com/stellargraph/stellargraph
Using C&CG to solve two-stage robust optimization