Lightning ⚡️ fast forecasting with statistical and econometric models.

A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

PyTorch code for ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Hierarchical Time Series Forecasting with a familiar API

Implementation of ETSformer, state of the art time-series Transformer, in Pytorch

A learning tool to demonstrate the process of financial forecasting, budgeting, and analysis.

Theta methods for time series forcasting

Time series regression modeling on a dataset of supermarket sales across years, with the Darts library in Python.

Keras, Tensorflow eager execution layers for exponential smoothing

A simple introduction to statistical learning for time-series forecasting using the Holt Simple Exponential Smoothing method

Model trials to filter orbital data

DSCI 524 Group 20: Python package that analyzes stocks!

A Python-based module for solving supply chain optimization problems and generating time-series forecasts. This project implements the Transportation Problem using Linear Programming (PuLP) and applies Exponential Smoothing for forecasting time-series data.

Real-time imputation of missing environmental sensor data for fault-tolerant edge computing.

SKU-level customer demand forecasts for SSDs for improved long-term supply planning

How to make forecast with python ? I develop a software that allows to : - Make commercial forecasts from a history - Compare several forecasting methods - Display the results (forecasts and comparison)

Data smoothing visualization

A new regularization technique by encountering samples through exponential smoothing

Developed a data analysis script to perform demand forecasting, improving supply chain efficiency by utilizing the ARIMA and the Exponential Smoothing models.

Third year university IoT module for monitoring heart health in diabetic patients. The system combines hardware sensors, real-time data processing, and machine learning analytics to detect anomalies and track vital sign trends. The results are then displayed in a Streamlit web page.