English | 2022 | ISBN: 978-1617299889 | 222 pages | pdf | 10.9 MB
Build predictive models from -based patterns in your data.
Master statistical models including new deep learning approaches for series forecasting.
Series Forecasting in Python teaches you to build powerful predictive models from -based data. Every model you create is relevant, useful, and easy to implement with Python. You'll explore interesting real-world datasets like Google's daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.
Series Forecasting in Python teaches you to apply series forecasting and get immediate, meaningful predictions. You'll learn both traditional statistical and new deep learning models for series forecasting, all fully illustrated with Python source code. Test your skills with hands-on projects for forecasting air travel, volume of drug prescriptions, and the earnings of Johnson & Johnson. By the you're done, you'll be ready to build accurate and insightful forecasting models with tools from the Python ecosystem.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
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