Active Machine Learning with Python

Active Machine Learning with Python equips you to harness the power of active learning to create robust machine learning models with minimal data. Through practical examples and step-by-step guidance, you'll learn how to implement active learning techniques to optimize workflows, minimize data labeling costs, and improve model performance with Python.

What this Book will help me do

• Develop a solid understanding of active learning fundamentals and strategies.
• Integrate Python libraries to streamline active learning workflows.
• Handle complexities such as data imbalance and concept drift in ML projects.
• Enhance model performance through optimal data selection techniques.
• Leverage active learning in real-world settings like computer vision and big data applications.

Author(s)

Margaux Masson-Forsythe is a seasoned machine learning engineer, with a strong focus on surgical data science and climate AI advancements. Her expertise in active learning and real-world machine learning implementations ensures a balanced and practical approach to teaching. She is dedicated to sharing actionable insights and making advanced machine learning concepts accessible to practitioners.

Who is it for?

This book is perfect for ML engineers and data scientists aiming to maximize their models' efficiency and performance while reducing data costs. Readers should have a foundational understanding of Python and basic machine learning concepts such as datasets and neural networks. It's tailored for those seeking practical knowledge and tools for enhancing machine learning projects through active learning.