List of papers, code and experiments using deep learning for time series forecasting
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Updated
Mar 16, 2024 - Jupyter Notebook
List of papers, code and experiments using deep learning for time series forecasting
Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
A curated list of awesome supply chain blogs, podcasts, standards, projects, and examples.
This project is a collection of recent research in areas such as new infrastructure and urban computing, including white papers, academic papers, AI lab and dataset etc.
Python sdk for zero-shot time-series forecasting
Full-stack Highly Scalable Cloud-native Machine Learning system for demand forecasting with realtime data streaming, inference, retraining loop, and more
Machine Learning for Retail Sales Forecasting — Features Engineering
Internship project
Time Series Forecasting for the M5 Competition
End-to-end demand forecasting with Python using synthetic time-series sales data. Includes data generation, cleaning, ARIMA/SARIMA model selection by AIC, evaluation with RMSE and MAPE, and 90-day forecasts with confidence intervals. Reproducible scripts and visualizations for portfolio showcase.
The primary objective of this project is to build a Real-Time Taxi Demand Prediction Model for every district and zone of NYC.
Time Series Forecasting Methods — A collection of Python implementations for essential time series forecasting techniques, including Simple, Double, Triple Exponential Smoothing, and Moving Averages.
E-commerce Inventory System developed using Vue and Vuetify
Dynamic Bandwidth Monitor; leak detection method implemented in a real-time data historian
This project focuses on Supply Chain Analytics and Demand Forecasting using advanced analytics and models to optimize operations and predict future demand.
Implement inventory management rules based on a periodic review policy
Energy Forecast Benchmark Toolkit is a Python project that aims to provide common tools to benchmark forecast models.
A project focused on YouBike optimization, including improvement of dispatch strategies and prediction of potential demand.
Bike sharing prediction based on neural nets
Code repository for the paper "Data-driven modelling of energy demand response behaviour based on a large-scale residential trial".
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