Machine Learning for Time-Series with Python
Ben Auffarth
Sold by Rarewaves USA United, OSWEGO, IL, U.S.A.
AbeBooks Seller since 20 June 2025
New - Soft cover
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Add to basketSold by Rarewaves USA United, OSWEGO, IL, U.S.A.
AbeBooks Seller since 20 June 2025
Condition: New
Quantity: Over 20 available
Add to basketThe book contains the most common as well as state-of-the-art methods in machine learning for time-series, and examples that every data scientist or analyst would have encountered, if not in their job, then in a job interview.
Seller Inventory # LU-9781801819626
Become proficient in deriving insights from time-series data and analyzing a model’s performance
Machine learning has emerged as a powerful tool to understand hidden complexities in time-series datasets, which frequently need to be analyzed in areas as diverse as healthcare, economics, digital marketing, and social sciences. These datasets are essential for forecasting and predicting outcomes or for detecting anomalies to support informed decision making.
This book covers Python basics for time-series and builds your understanding of traditional autoregressive models as well as modern non-parametric models. You will become confident with loading time-series datasets from any source, deep learning models like recurrent neural networks and causal convolutional network models, and gradient boosting with feature engineering.
Machine Learning for Time-Series with Python explains the theory behind several useful models and guides you in matching the right model to the right problem. The book also includes real-world case studies covering weather, traffic, biking, and stock market data.
By the end of this book, you will be proficient in effectively analyzing time-series datasets with machine learning principles.
This book is ideal for data analysts, data scientists, and Python developers who are looking to perform time-series analysis to effectively predict outcomes. Basic knowledge of the Python language is essential. Familiarity with statistics is desirable.
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