whyisshizai/LSTM-Transformer-Time-Series-Forecasting
A Hybrid LSTM-Transformer Network for Local and Global Planning
This tool helps predict future values in time-series data by combining two neural network approaches. You input your sequential data, like sensor readings or stock prices, and it outputs predictions for what will happen next. It's designed for data scientists or analysts who need accurate forecasts for planning and decision-making.
No commits in the last 6 months.
Use this if you need to forecast time-series data, especially when both short-term fluctuations and long-range patterns are important for accurate predictions.
Not ideal if your data doesn't have a sequential or time-dependent nature, or if you need to understand the causal relationships between variables rather than just predicting future values.
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Python
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Last pushed
Mar 17, 2025
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