WildGenie / Machine-Learning-for-Time-Series-with-Python

Machine Learning for Time-Series with Python.Published by Packt

Machine-Learning-for-Time-Series-with-Python

Become proficient in deriving insights from time-series data and analyzing a model’s performance

Links

• Amazon
• Packt Publishing

Key Features

• Explore popular and modern machine learning methods including the latest online and deep learning algorithms
• Learn to increase the accuracy of your predictions by matching the right model with the right problem
• Master time-series via real-world case studies on operations management, digital marketing, finance, and healthcare

What you will learn

• Understand the main classes of time-series and learn how to detect outliers and patterns
• Choose the right method to solve time-series problems
• Characterize seasonal and correlation patterns through autocorrelation and statistical techniques
• Get to grips with time-series data visualization
• Understand classical time-series models like ARMA and ARIMA
• Implement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning models
• Become familiar with many libraries like Prophet, XGboost, and TensorFlow

Who This Book Is For

This book is ideal for data analysts, data scientists, and Python developers who are looking to perform time-series analysis to effectively predict outcomes. Basic knowledge of the Python language is essential. Familiarity with statistics is desirable.

Table of Contents

1. Introduction to Time-Series with Python
2. Time-Series Analysis with Python
3. Preprocessing Time-Series
4. Introduction to Machine Learning for Time-Series
5. Forecasting with Moving Averages and Autoregressive Models
6. Unsupervised Methods for Time-Series
7. Machine Learning Models for Time-Series
8. Online Learning for Time-Series
9. Probabilistic Models for Time-Series
10. Deep Learning for Time-Series
11. Reinforcement Learning for Time-Series
12. Multivariate Forecasting

Author Notes

I've heard from a few people struggling with tsfresh and featuretools for chapter 3.

My PR for tsfresh was merged mid-December fixing a version incompatibility - featuretools went through many breaking changes with the release of version 1.0.0 (congratulations to the team!). Please see how to fix any problems in the discussion here.

Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

https://packt.link/free-ebook/9781801819626