Machine Learning for Streaming Data with Python

Dive into the burgeoning field of streaming data analysis with "Machine Learning for Streaming Data with Python." This book gets you acquainted with adapting machine learning techniques to handle real-time data streams effectively. Utilizing Python and tools like River, you'll learn innovative solutions with practical applications.

What this Book will help me do

• Gain proficiency in working with the River framework for machine learning on streaming data.
• Understand and mitigate challenges unique to streaming data processing.
• Design and implement robust architectures for real-time machine learning use cases.
• Develop real-time anomaly detection and online learning models.
• Explore reinforcement learning, drift detection, and feature transformation for streaming contexts.

Author(s)

Joos Korstanje, the author of this compelling book, is a seasoned data scientist with extensive experience in building machine learning solutions. Joos has a reputation for demystifying complex topics in data science and translating them into actionable knowledge. With a focus on practical implementations, Joos blends theory and practice to empower readers to excel in their technical journeys.

Who is it for?

This book is tailored for data scientists and machine learning engineers with a foundational understanding of Python and machine learning concepts and a keen interest in advancing into real-time or streaming data systems. It is ideal for practitioners willing to explore the specific challenges and opportunities of streaming data and craving hands-on examples to handle it skillfully.