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Active Machine Learning with Python: Refine and elevate data quality over quantity with active learning by Margaux Masson-Forsythe instant download

  • SKU: EBN-237054100
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Instant download (eBook) Active Machine Learning with Python: Refine and elevate data quality over quantity with active learning after payment.
Authors:Margaux Masson-Forsythe
Pages:176 pages
Year:2024
Edition:1
Publisher:Packt Publishing
Language:english
File Size:15.5 MB
Format:pdf
Categories: Ebooks

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Active Machine Learning with Python: Refine and elevate data quality over quantity with active learning by Margaux Masson-Forsythe instant download

TRUE PDF

Use active machine learning with Python to improve the accuracy of predictive models, streamline the data analysis process, and adapt to evolving data trends, fostering innovation and progress across diverse fields
 
Key benefits
• Learn how to implement a pipeline for optimal model creation from large datasets and at lower costs
• Gain profound insights within your data while achieving greater efficiency and speed
• Apply your knowledge to real-world use cases and solve complex ML problems
 
Preface
Welcome to Active Learning with Python a comprehensive guide designed to introduce you to the power of active machine learning. This book is written with the conviction that while data is plentiful, its quality and relevance hold the key to building models that are not only efficient but also robust and insightful.
 
Active machine learning is a method used in machine learning where the algorithm can query an oracle to label new data points with the desired outputs. It stands at the crossroads of optimization and human-computer interaction, enabling machines to learn more effectively with less data. This is particularly valuable in scenarios where data labeling is costly, time-consuming, or requires expert knowledge.
 
Throughout this book, we leverage Python, a leading programming language in the field of data science and machine learning, known for its simplicity and powerful libraries. Python serves as an excellent medium for exploring the concepts of active machine learning, providing both beginners and experienced practitioners with the tools needed to implement sophisticated models.
 
Who this book is for
This book is intended for data scientists, machine learning engineers, researchers, and anyone curious about optimizing machine learning workflows. Whether you are new to active machine learning or looking to enhance your current models, this book provides insights into making the most of your data through strategic querying and learning techniq
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