Modern Time Series Forecasting with Python

Modern Time Series Forecasting with Python
Author :
Publisher : Packt Publishing Ltd
Total Pages : 552
Release :
ISBN-10 : 9781803232041
ISBN-13 : 1803232048
Rating : 4/5 (41 Downloads)

Book Synopsis Modern Time Series Forecasting with Python by : Manu Joseph

Download or read book Modern Time Series Forecasting with Python written by Manu Joseph and published by Packt Publishing Ltd. This book was released on 2022-11-24 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep learning concepts Key Features Explore industry-tested machine learning techniques used to forecast millions of time series Get started with the revolutionary paradigm of global forecasting models Get to grips with new concepts by applying them to real-world datasets of energy forecasting Book DescriptionWe live in a serendipitous era where the explosion in the quantum of data collected and a renewed interest in data-driven techniques such as machine learning (ML), has changed the landscape of analytics, and with it, time series forecasting. This book, filled with industry-tested tips and tricks, takes you beyond commonly used classical statistical methods such as ARIMA and introduces to you the latest techniques from the world of ML. This is a comprehensive guide to analyzing, visualizing, and creating state-of-the-art forecasting systems, complete with common topics such as ML and deep learning (DL) as well as rarely touched-upon topics such as global forecasting models, cross-validation strategies, and forecast metrics. You’ll begin by exploring the basics of data handling, data visualization, and classical statistical methods before moving on to ML and DL models for time series forecasting. This book takes you on a hands-on journey in which you’ll develop state-of-the-art ML (linear regression to gradient-boosted trees) and DL (feed-forward neural networks, LSTMs, and transformers) models on a real-world dataset along with exploring practical topics such as interpretability. By the end of this book, you’ll be able to build world-class time series forecasting systems and tackle problems in the real world.What you will learn Find out how to manipulate and visualize time series data like a pro Set strong baselines with popular models such as ARIMA Discover how time series forecasting can be cast as regression Engineer features for machine learning models for forecasting Explore the exciting world of ensembling and stacking models Get to grips with the global forecasting paradigm Understand and apply state-of-the-art DL models such as N-BEATS and Autoformer Explore multi-step forecasting and cross-validation strategies Who this book is for The book is for data scientists, data analysts, machine learning engineers, and Python developers who want to build industry-ready time series models. Since the book explains most concepts from the ground up, basic proficiency in Python is all you need. Prior understanding of machine learning or forecasting will help speed up your learning. For experienced machine learning and forecasting practitioners, this book has a lot to offer in terms of advanced techniques and traversing the latest research frontiers in time series forecasting.


Modern Time Series Forecasting with Python Related Books

Modern Time Series Forecasting with Python
Language: en
Pages: 552
Authors: Manu Joseph
Categories: Computers
Type: BOOK - Published: 2022-11-24 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Build real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep learning concepts Key Featu
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
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
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