Machine Learning for Time-Series with Python

Machine Learning for Time-Series with Python
Author :
Publisher : Packt Publishing Ltd
Total Pages : 371
Release :
ISBN-10 : 9781801816106
ISBN-13 : 1801816107
Rating : 4/5 (06 Downloads)

Book Synopsis Machine Learning for Time-Series with Python by : Ben Auffarth

Download or read book Machine Learning for Time-Series with Python written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2021-10-29 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get better insights from time-series data and become proficient in model performance analysis Key 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.


Machine Learning for Time-Series with Python Related Books

Machine Learning for Time-Series with Python
Language: en
Pages: 371
Authors: Ben Auffarth
Categories: Computers
Type: BOOK - Published: 2021-10-29 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Get better insights from time-series data and become proficient in model performance analysis Key FeaturesExplore popular and modern machine learning methods in
Machine Learning for Time Series Forecasting with Python
Language: en
Pages: 224
Authors: Francesca Lazzeri
Categories: Computers
Type: BOOK - Published: 2020-12-03 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with
Deep Learning for Time Series Forecasting
Language: en
Pages: 572
Authors: Jason Brownlee
Categories: Computers
Type: BOOK - Published: 2018-08-30 - Publisher: Machine Learning Mastery

DOWNLOAD EBOOK

Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of te
Introduction to Time Series Forecasting With Python
Language: en
Pages: 359
Authors: Jason Brownlee
Categories: Mathematics
Type: BOOK - Published: 2017-02-16 - Publisher: Machine Learning Mastery

DOWNLOAD EBOOK

Time series forecasting is different from other machine learning problems. The key difference is the fixed sequence of observations and the constraints and addi
Time Series Forecasting in Python
Language: en
Pages: 454
Authors: Marco Peixeiro
Categories: Computers
Type: BOOK - Published: 2022-11-15 - Publisher: Simon and Schuster

DOWNLOAD EBOOK

Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. In