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Packt Publishing 2021 paperback Good Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! [Dallas, TX, U.S.A.] [Publication Year: 2021]
New. New Book; Fast Shipping from UK; Not signed; Not First Edition; The Machine Learning for Time-Series with Python: Forecast, predict, and detect anomalies with state-of-the-art machine learning methods. ISBN 1801819629 9781801819626 [GB]
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover Special order direct from the distributor [Victoria, BC, Canada] [Publication Year: 2021]
Packt Publishing Limited 10/29/2021 12: 00: 00 AM Softcover PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover Buy with confidence! Book is in good condition with minor wear to the pages, binding, and minor marks within [Amherst, NY, U.S.A.] [Publication Year: 2021]
Paperback / softback. New. The 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. ISBN 1801819629 9781801819626 [GB]
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover Book is in Used-LikeNew condition. Pages and cover are clean and intact. Used items may not include supplementary materials such as CDs or access codes. May show signs of minor shelf wear. [Hawthorne, CA, U.S.A.] [Publication Year: 2021]
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover Like New condition. Great condition, but not exactly fully crisp. The book may have been opened and read, but there are no defects to the book, jacket or pages. [Tucson, AZ, U.S.A.] [Publication Year: 2021]
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover Book is in NEW condition. [Hawthorne, CA, U.S.A.] [Publication Year: 2021]
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover New! This book is in the same immaculate condition as when it was published [Tucson, AZ, U.S.A.] [Publication Year: 2021]
Packt Publishing Limited 10/29/2021 12: 00: 00 AM Softcover PLEASE NOTE, WE DO NOT SHIP TO DENMARK. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Please note we cannot offer an expedited shipping service from the UK.
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover nach der Bestellung gedruckt Neuware - Printed after ordering - Become proficient in deriving insights from time-series data and analyzing a model's performanceKey Features:Explore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time-series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description: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 proble ...
ISBN10: 1801819629, ISBN13: 9781801819626, [publisher: Packt Publishing] Softcover New [Long Beach, CA, U.S.A.] [Publication Year: 2021]
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