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ASIN : B0D6G3SHD6
Publisher : Packt Publishing; 2nd ed. edition (October 31, 2024)
Language : English
Paperback : 658 pages
ISBN-10 : 1835883184
ISBN-13 : 978-1835883181
Item Weight : 3.03 pounds
Dimensions : 1.41 x 7.5 x 9.25 inches
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Time series forecasting is a crucial task in many industries, from finance to marketing to healthcare. With the advent of machine learning and deep learning, the field of time series forecasting has been revolutionized. In this post, we will explore how to perform industry-ready time series analysis using Python, PyTorch, and pandas.
PyTorch is a popular deep learning library that provides a flexible and efficient platform for building and training neural networks. pandas is a powerful data manipulation library that is widely used for working with time series data. By combining these two libraries, we can create powerful and accurate time series forecasting models.
In this post, we will cover the following topics:
1. Preprocessing time series data using pandas
2. Building machine learning models for time series forecasting
3. Implementing deep learning models for time series forecasting with PyTorch
4. Evaluating the performance of time series forecasting models
5. Deploying industry-ready time series forecasting models
By the end of this post, you will have a solid understanding of how to leverage Python, PyTorch, and pandas to perform advanced time series forecasting for a wide range of industries. Stay tuned for our upcoming tutorials on this topic!
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