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Time Series Forecasting in Python

Published by Manning
Distributed by Simon & Schuster

Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting.

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.

Time Series Forecasting in Python teaches you to apply time series forecasting and get immediate, meaningful predictions. You’ll learn both traditional statistical and new deep learning models for time 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 time 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.

Marco Peixeiro is a seasoned data science instructor who has worked as a data scientist for one of Canada’s largest banks. He is an active contributor to Towards Data Science, an instructor on Udemy, and on YouTube in collaboration with freeCodeCamp.