Book description
- Implement various techniques in time series analysis using Python.
- Utilize statistical modeling methods such as AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average) and ARIMA (autoregressive integrated moving-average) for time series forecasting
- Understand univariate and multivariate modeling for time series forecasting
- Forecast using machine learning and deep learning techniques such as GBM and LSTM (long short-term memory)
Product information
- Title: Time Series Algorithms Recipes: Implement Machine Learning and Deep Learning Techniques with Python
- Author(s):
- Release date: December 2022
- Publisher(s): Apress
- ISBN: 9781484289785
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