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

Investigation of the capabilities of foundations models in the context of time series forecasting

Analyze and propose the plan to monitor and estimate business aspects

Solar Irradiance Forecasting Using Deep Learning Techniques

Analysis Sales data to gain insights and create Interactive Sales Dashboard and also predict /Forecast the next sales with the use of Power-Bi.

Dhaka weather forecasting model trained using API from Open-Meteo.com

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)

Exploring forecasting for energy consumption

Analyzing retail sales data to craft targeted marketing, elevate customer experiences, and forecast future sales.

In this section, we will use machine learning algorithms to perform time series analysis.

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.

💲 🔮 Predict 3 months of item-level sales data at different store locations and optimize budgets and placements to maximize key product metrics

A project from dicoding Machine Learning Intermediate Class with data Time Series

The day-ahead prediction of electricity production from a run-of-river hydropower plant.

A multivariate time series forecasting of pollution data using ARIMA, LM & ARIMAX in R

Highly accurate forecasting model for predicting Bitcoin prices in January 2024 using deep learning techniques, specifically Recurrent Neural Networks (RNNs).

Forecasting EEG signals using Lag-Llama model