Machine Learning for Time Series with Python - Second Edition

"Machine Learning for Time-Series with Python" is your definitive guide to mastering the challenges of time-series data analysis and forecasting. Through this book, you will learn how to handle various time-series tasks using modern Python libraries and state-of-the-art machine learning techniques.

What this Book will help me do

• Learn to visualize and preprocess time-series data effectively.
• Gain proficiency in working with classical models like ARIMA and contemporary ones like gradient boosting.
• Understand how and when to apply deep learning models for time-series problems.
• Master the usage of top Python libraries, including TensorFlow and Prophet, for time-series tasks.
• Navigate real-world applications in finance, healthcare, and marketing with practical case studies.

Author(s)

Ben Auffarth, the author of this book, is an accomplished data scientist and machine learning expert with a passion for time-series modeling. With a strong academic background and years of practical experience, Ben conveys complex topics in an accessible and practical manner. His goal is to empower readers to confidently handle time-series challenges using cutting-edge tools.

Who is it for?

This book is perfect for data analysts, data scientists, and Python developers aiming to deepen their expertise in time-series analysis. If you're at an intermediate level in Python and have some foundational knowledge of statistics, you'll find this book especially approachable and immensely beneficial for advancing your skills.