Code repository for the online course "Feature Engineering for Time Series Forecasting".
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Updated
Dec 6, 2023 - Jupyter Notebook
Code repository for the online course "Feature Engineering for Time Series Forecasting".
The official code for "TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)". TEMPO is one of the very first open source Time Series Foundation Models for forecasting task v1.0 version.
Forecasting Time Series with Moving Average and Exponential Smoothing
Official repo for the following paper: Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training (SCPT) (ECML PKDD DAMI '23)
Investigation of the capabilities of foundations models in the context of time series forecasting
Automatically select DNNs for time series forecasting under consideration of complexity and resource consumption.
Analysis Sales data to gain insights and create Interactive Sales Dashboard and also predict /Forecast the next sales with the use of Power-Bi.
Analyze and propose the plan to monitor and estimate business aspects
Solar Irradiance Forecasting Using Deep Learning Techniques
Dhaka weather forecasting model trained using API from Open-Meteo.com
data and code associated with the publication "Age structure augments the predictive power of time series for fisheries and conservation" by Tara E. Dolan, Eric P. Palkovacs, Tanya L. Rogers, and Stephan B. Munch.
Analyzing retail sales data to craft targeted marketing, elevate customer experiences, and forecast future sales.
Exploring forecasting for energy consumption
Two projects developed as part of a university course on Artificial Neural networks and Deep Learning, in particular, an image classification task, and a univariate time series forecasting task.
Implementing method of Willemain et al., 2004 for forecasting intermittent demand
In this section, we will use machine learning algorithms to perform time series analysis.
An Implementation of N-BEATS using Pytorch Lightning
Learn about how we can use models to make predicitons in the future based on historical data.
Repository for replicating and comparing time series LLM models with statistical models
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