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Key benefits

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

Description

We 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.

Who is this book 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.

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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

Machine Learning with PyTorch and Scikit-Learn

$54.99

Time Series Analysis with Python Cookbook

$51.99

Modern Time Series Forecasting with Python

$52.99

Total $ 159.97

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Machiel Kruger Feb 22, 2024

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Kumar A. Dec 02, 2022

It covers all the aspects of modern time series forecasting. The worked examples are easy to understand and explains the concepts well.This book will help practitioners who will be working with real world time series forecasting problems. Candidates will also find it useful for interview preparations in this field.

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Faris Jul 06, 2023

Well written, explainations are detailed enough to get you where you need to go.

Kindle Customer Dec 25, 2022

The book takes the reader on a journey from the most basic of TS concepts and models, all the way to the advanced level.The best part about the book for me is that, the author has not just explained the topics but has also tried to equip the reader with the tools and explanations, that can help one understand the concepts intuitively. Have come across many books that leave you with the formulas, but not many that bring them home. This book bridges that gap to a very large extent.10/10 a must read!

yedunathan May 10, 2023

This is a great book for any who wants to learn practical approach to time series.This book addresses the domain specific challenges as well very clearly.

Modern Time Series Forecasting with Python: Explore industry-ready time series forecasting using modern machine learning and deep learning

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