Description: Further DetailsTitle: Machine Learning for Time-Series with PythonCondition: NewSubtitle: Forecast, predict, and detect anomalies with state-of-the-art machine learning methodsEAN: 9781801819626ISBN: 9781801819626Publisher: Packt Publishing LimitedFormat: PaperbackRelease Date: 10/29/2021Description: Get better insights from time-series data and become proficient in model performance analysisKey FeaturesExplore 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 The Python time-series ecosystem is huge and often quite hard to get a good grasp on, especially for time-series since there are so many new libraries and new models. This book aims to deepen your understanding of time series by providing a comprehensive overview of popular Python time-series packages and help you build better predictive systems. Machine Learning for Time-Series with Python starts by re-introducing the basics of time series and then builds your understanding of traditional autoregressive models as well as modern non-parametric models. By observing practical examples and the theory behind them, 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. This book will also guide you in matching the right model to the right problem by explaining the theory behind several useful models. You’ll also have a look at real-world case studies covering weather, traffic, biking, and stock market data. By the end of this book, you should feel at home with effectively analyzing and applying machine learning methods to time-series.What you will learnUnderstand the main classes of time series and learn how to detect outliers and patternsChoose the right method to solve time-series problemsCharacterize seasonal and correlation patterns through autocorrelation and statistical techniquesGet to grips with time-series data visualizationUnderstand classical time-series models like ARMA and ARIMAImplement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning modelsBecome familiar with many libraries like Prophet, XGboost, and TensorFlowWho this book is for This book is ideal for data analysts, data scientists, and Python developers who want instantly useful and practical recipes to implement today, and a comprehensive reference book for tomorrow. Basic knowledge of the Python Programming language is a must, while familiarity with statistics will help you get the most out of this book.Language: EnglishCountry/Region of Manufacture: GBItem Height: 93mmItem Length: 75mmAuthor: Ben AuffarthGenre: Computing & InternetISBN-10: 1801819629Release Year: 2021 Missing Information?Please contact us if any details are missing and where possible we will add the information to our listing.
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Book Title: Machine Learning for Time-Series with Python
Title: Machine Learning for Time-Series with Python
Subtitle: Forecast, predict, and detect anomalies with state-of-the-art mac
EAN: 9781801819626
ISBN: 9781801819626
Release Date: 10/29/2021
Release Year: 2021
Country/Region of Manufacture: GB
Item Height: 93mm
Genre: Computing & Internet
ISBN-10: 1801819629
Number of Pages: 370 Pages
Language: English
Publication Name: Machine Learning for Time-Series with Python : Forecast, Predict, and Detect Anomalies with State-Of-the-art Machine Learning Methods
Publisher: Packt Publishing, The Limited
Subject: Data Modeling & Design, Intelligence (Ai) & Semantics, General, Programming Languages / Python
Publication Year: 2021
Type: Textbook
Author: Ben Auffarth
Subject Area: Computers, Science
Item Length: 3.6 in
Item Width: 3 in
Format: Trade Paperback
