ISBN: 9798292154167 - time series forecasting with python: deploying and managing machine learning models in production (9 risultati)

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  • Lingua: Inglese

    Editore: Independently published, 2025

    9798292154167

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    Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices

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  • Lingua: Inglese

    Editore: Independently published, 2025

    9798292154167

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  • Lingua: Inglese

    Editore: Independently published, 2025

    9798292154167

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: Independently published, 2025

    9798292154167

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: Independently Published, 2025

    9798292154167

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    Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

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    Paperback. Condizione: new. Paperback. Master time series forecasting and bring your machine learning models into production.Time Series Forecasting with Python is the essential guide to building and deploying time series models with Python. Whether you're predicting stock prices, sales forecasts, or weather patterns, this book shows you how to develop robust models and get them into production, seamlessly integrating them into real-world applications.You'll learn how to apply machine learning algorithms for time series forecasting, fine-tune models for accuracy, and take them from development to live deployment-while handling challenges like data drift and performance monitoring.Inside, you'll learn how to: Understand the fundamentals of time series data and forecastingPreprocess and clean time series data for modelingBuild and evaluate forecasting models using ARIMA, Prophet, and LSTMApply machine learning techniques like XGBoost and Random Forest to time series dataUse Python libraries like pandas, statsmodels, and scikit-learnAutomate forecasting with pipelines and batch predictionsDeploy models to cloud platforms like AWS, Google Cloud, or AzureMonitor model performance in production, and update models as neededIntegrate time series forecasting into real-world applications like dashboards and APIsWith hands-on examples, complete code snippets, and deployment tips, you'll be able to take your forecasting models from prototype to production and ensure they continue to perform well in a dynamic environment.Whether you're a data scientist, software engineer, or business analyst, Time Series Forecasting with Python equips you with the tools to solve complex forecasting problems and deploy reliable models at scale. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

  • Lingua: Inglese

    Editore: Independently published, 2025

    9798292154167

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    Da: California Books, Miami, FL, U.S.A.California Books

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    EUR 22,96

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  • Lingua: Inglese

    Editore: Amazon Digital Services LLC - Kdp, 2025

    9798292154167

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    Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US

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    PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Lingua: Inglese

    Editore: Amazon Digital Services LLC - Kdp, 2025

    9798292154167

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    Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK

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    PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Lingua: Inglese

    Editore: Independently Published, 2025

    9798292154167

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    Da: CitiRetail, Stevenage, Regno UnitoCitiRetail

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    EUR 25,59

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    Paperback. Condizione: new. Paperback. Master time series forecasting and bring your machine learning models into production.Time Series Forecasting with Python is the essential guide to building and deploying time series models with Python. Whether you're predicting stock prices, sales forecasts, or weather patterns, this book shows you how to develop robust models and get them into production, seamlessly integrating them into real-world applications.You'll learn how to apply machine learning algorithms for time series forecasting, fine-tune models for accuracy, and take them from development to live deployment-while handling challenges like data drift and performance monitoring.Inside, you'll learn how to: Understand the fundamentals of time series data and forecastingPreprocess and clean time series data for modelingBuild and evaluate forecasting models using ARIMA, Prophet, and LSTMApply machine learning techniques like XGBoost and Random Forest to time series dataUse Python libraries like pandas, statsmodels, and scikit-learnAutomate forecasting with pipelines and batch predictionsDeploy models to cloud platforms like AWS, Google Cloud, or AzureMonitor model performance in production, and update models as neededIntegrate time series forecasting into real-world applications like dashboards and APIsWith hands-on examples, complete code snippets, and deployment tips, you'll be able to take your forecasting models from prototype to production and ensure they continue to perform well in a dynamic environment.Whether you're a data scientist, software engineer, or business analyst, Time Series Forecasting with Python equips you with the tools to solve complex forecasting problems and deploy reliable models at scale. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …