https://github.com/sushantdhumak/lstm_for_household_power_consumption
This project explores the application of Long Short-Term Memory (LSTM) networks in predicting household power consumption. Using data collected at one-minute intervals, we demonstrate how LSTM can be leveraged for accurate forecasting.
https://github.com/sushantdhumak/lstm_for_household_power_consumption
correlation-analysis data-visualization dropout evaluation-metrics feature-engineering lstm lstm-model resampling reshaping-datasets time-series-analysis time-series-forecasting
Last synced: 6 months ago
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This project explores the application of Long Short-Term Memory (LSTM) networks in predicting household power consumption. Using data collected at one-minute intervals, we demonstrate how LSTM can be leveraged for accurate forecasting.
- Host: GitHub
- URL: https://github.com/sushantdhumak/lstm_for_household_power_consumption
- Owner: sushantdhumak
- Created: 2025-01-09T05:22:01.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-01-09T05:28:53.000Z (9 months ago)
- Last Synced: 2025-01-30T23:05:55.975Z (8 months ago)
- Topics: correlation-analysis, data-visualization, dropout, evaluation-metrics, feature-engineering, lstm, lstm-model, resampling, reshaping-datasets, time-series-analysis, time-series-forecasting
- Language: Jupyter Notebook
- Homepage:
- Size: 5.32 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0