Modern Time Series Forecasting with Python: Exploring statistical models, machine learning, and deep learning for cutting-edge time series forecasting (English Edition)

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Hands-on exploration of time series fundamentals enables a solid conceptual foundation
Covers ARIMA, SARIMA, Holt-Winters, and machine learning models for versatile forecasting
Deep learning chapters introduce RNNs, LSTMs, and CNN-LSTM architectures for advanced predictions
Includes deployment techniques with FastAPI, Apache Kafka, and Dask for scalable model management
Walk-forward validation and error metric analysis ensure robust, production-ready models

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4.8 (34K)

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Hands-on exploration of time series fundamentals enables a solid conceptual foundation
Covers ARIMA, SARIMA, Holt-Winters, and machine learning models for versatile forecasting
Deep learning chapters introduce RNNs, LSTMs, and CNN-LSTM architectures for advanced predictions
Includes deployment techniques with FastAPI, Apache Kafka, and Dask for scalable model management
Walk-forward validation and error metric analysis ensure robust, production-ready models

Summarized by Shop

Visit Barnes & Noble for full shipping details

Shipping calculated at checkout

4.8 (34K)

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