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Ridwan Halim

Electricity Demand Forecaster

Tap into RNNs to nail super-accurate electricity demand predictions.

Python Python
PyTorch PyTorch
Electricity Demand Forecaster

Project Description

This project rocks Recurrent Neural Networks (RNNs) like LSTM and GRU to forecast electricity demand with serious precision.

Trained on historical demand data, mixed with weather and calendar features for max accuracy.

Perfect for showcasing how RNNs can level up energy management with killer temporal insights.

Key Features

RNN Powerhouse

LSTM and GRU models crush it at capturing time-based patterns.

Loaded Dataset

Blends historical demand, weather, and calendar data for sharp predictions.

Energy Game-Changer

Delivers spot-on forecasts for real-world energy planning.

Technical Details

Python

My go-to for building robust backends with clean code

PyTorch

Open-source machine learning library for Python, great for deep learning

RNN

Recurrent Neural Networks for sequence prediction tasks

LSTM

Long Short-Term Memory networks for time series and sequence data

GRU

Gated Recurrent Units for efficient sequence modeling