Requirements: .ePUB reader, 17 mb
Overview: Time Series Forecasting in Python teaches you how to get immediate, meaningful predictions from time-based data such as logs, customer analytics, and other event streams. In this accessible book, you’ll learn statistical and deep learning methods for time series forecasting, fully demonstrated with annotated Python code. Develop your skills with projects like predicting the future volume of drug prescriptions, and you’ll soon be ready to build your own accurate, insightful forecasts.
Genre: Non-Fiction > Tech & Devices
In Time Series Forecasting in Python you will learn how to
• Recognize a time series forecasting problem and build a performant predictive model
• Create univariate forecasting models that account for seasonal effects and external variables
• Build multivariate forecasting models to predict many time series at once
• Leverage large datasets by using deep learning for forecasting time series
• Automate the forecasting process
Time Series Forecasting in Python teaches you to build powerful predictive models from time-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.
Download Instructions:
https://ouo.io/e6qxYmJ
Mirror:
http://2bay.org/6de038eb88363b12ae0e56e … 8f9f35ab92.
