Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy, bìa mềm
Predicting the future, whether it's market trends,
energy demand, or website traffic, has never been more crucial. This
practical, hands-on guide empowers you to build and deploy powerful time
series forecasting models. Whether you’re working with traditional
statistical methods or cutting-edge deep learning architectures, this
book provides structured learning and best practices for both.
Starting
with the basics, this data science book introduces fundamental time
series concepts, such as ARIMA and exponential smoothing, before
gradually progressing to advanced topics, such as machine learning for
time series, deep neural networks, and transformers. As part of your
fundamentals training, you’ll learn preprocessing, feature engineering,
and model evaluation. As you progress, you’ll also explore global
forecasting models, ensemble methods, and probabilistic forecasting
techniques.
This new edition goes deeper into transformer
architectures and probabilistic forecasting, including new content on
the latest time series models, conformal prediction, and hierarchical
forecasting. Whether you seek advanced deep learning insights or
specialized architecture implementations, this edition provides
practical strategies and new content to elevate your forecasting skills.
What you will learn
Build machine learning models for regression-based time series forecasting
Apply powerful feature engineering techniques to enhance prediction accuracy
Tackle common challenges like non-stationarity and seasonality
Combine multiple forecasts using ensembling and stacking for superior results
Explore cutting-edge advancements in probabilistic forecasting and handle intermittent or sparse time series
Evaluate and validate your forecasts using best practices and statistical metrics
Thể loại:Computers - Programming
Năm:2024
In lần thứ:2
Ngôn ngữ:english
Trang:659
