Keeping Inventory of spare in various service centre to the market demand is always a challenge as most service centres spends significant amount in spare parts inventory costs. In spite of this, availability of spare parts is been one of the problem areas.

Wave-Mask/Mix: Exploring Wavelet-Based Augmentations for Time Series Forecasting

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

End-to-end data pipeline analyzing 41GB (15B views) of Wikimedia telemetry via out-of-core DuckDB. Quantifies system volatility, filters statistical noise, and deploys a serverless interactive dashboard.

A repository containing 8 alpha signals with a signal combination engine incorporate a risk model, with 76+ automated tests.

Hybrid Ridge + LightGBM pipeline over 95k+ half-hourly demand records. Engineered Fourier seasonality, lag, and rolling-window features.

Dynamic Mode Decomposition for EEG signal analysis - Extract spatio-temporal coherent patterns from neural recordings

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Time Series Analysis and Stock Price Prediction of Reliance Industries using ARIMA (1, 1, 0) in Python.

Prediction of road casualties and evaluate the impact of transformations in Time Series Modeling and Forecasting with ARIMA using the R programming language

This repository demonstrates an end-to-end CTR time-series forecasting pipeline using SARIMA model. It analyzes daily advertising performance to uncover trend, weekly seasonality, and engagement patterns, and delivers 30-day forecasts to support budgeting, pacing, and marketing decision-making.

Teaching Lab Notes of "Time Series Analysis"@NTUsg by Patrick PUN Chi Seng

Internet Traffic Prediction Using Time Series Forecasting Models SARIMA and LSTMModels

Analyzing Marketing Resilience During the Pandemic Era

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This project explores retail chain performance in New Zealand by combining sales forecasting, regional sales analysis, and supply chain insights. Using real data and Python (including Prophet for forecasting), it uncovers patterns and helps identify areas for improvement in inventory and operations.

High-recall solar flare early warning system using GOES X-ray data, trained on PARAM Utkarsh HPC and deployed with Streamlit.

This is the task-1 of let's grow more virtual internship program. The aim of the task is as a security/defense analyst, try to find out the hot zone of terrorism.

Nerding out to understand stationarity, validate time series models, compare ARIMA vs ML, avoid data leakage

A comprehensive time series analysis project that forecasts monthly accidental deaths in the USA using statistical models. This project demonstrates exponential smoothing and ARIMA modeling techniques to predict future values based on historical data from January 1973 to December 1978.