Time-series demand forecasting is constructed by using LSTM, GRU, LSTM with seq2seq architecture, and prophet models.
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Jan 27, 2021 - Jupyter Notebook
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airline-passengers
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Determining the important factors that influences the customer or passenger satisfaction of an airlines using CRISP-DM methodology in Python and RapidMiner.
python random-forest exploratory-data-analysis jupyter-notebook naive-bayes-classifier logistic-regression decision-tree-classifier customer-satisfaction factors knn-classification rapidminer xgboost-algorithm crisp-dm airline-passengers adaboost-classifier passenger-satisfaction airline-passenger-satisfaction
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Sep 1, 2023 - Jupyter Notebook
In this section, we will examine the use of the prophet method, which is one of the time series analysis methods.
time-series prophet time-series-analysis time-series-prediction time-series-forecasting prophet-model airline-passengers prophet-facebook prophet-library prophet-facebook-model
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Apr 18, 2023 - Jupyter Notebook
Forecast monthly airline passenger demand using classical time series models — Holt-Winters, ARIMA, and SARIMAX. Analyze trends, seasonality, and model performance to identify the most accurate forecasting technique for real-world airline data.
python machine-learning time-series jupyter-notebook data-visualization forecasting data-analysis arima statsmodels sarimax holt-winters trend-analysis seasonality airline-passengers
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Nov 11, 2025 - Jupyter Notebook
This project aims to provide an explanation of how to apply the ARIMA model using Python to assist readers.
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Jan 22, 2025 - Jupyter Notebook
DL projects done in Python
deep-learning cross-validation recurrent-neural-networks neural-networks artificial-neural-networks data-preprocessing rnn-tensorflow breast-cancer-wisconsin breast-cancer chi-square-test time-series-forecasting one-hot-encoding airline-passengers
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Mar 12, 2024 - Jupyter Notebook
📈 Generate accurate demand forecasts with Python using synthetic data, featuring ARIMA/SARIMA modeling, evaluation metrics, and reproducible visualizations.
python demand energy time-series hls gru forecasting logistics regression-models mfg spatio-temporal-modeling airline-booking electricity-load-forecasting time-series-forecasting lstm-attention cnn-lstm airline-passengers gluonts
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Dec 16, 2025 - Python
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