Active Machine Learning with Python - Refine and Elevate Data Quality over Quantity with Active Learning

Building accurate machine learning models requires quality data-lots of it. However, for most teams, assembling massive datasets is time-consuming, expensive, or downright impossible. Led by author, a seasoned ML engineer and advocate for surgical data science and climate AI advancements, this hands...

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Bibliographische Detailangaben
1. Verfasser: Masson-Forsythe Margaux
Format: E-Book
Sprache:Englisch
Veröffentlicht: Birmingham Packt Publishing 2024
Packt Publishing, Limited
Ausgabe:1
Schlagworte:
Data mining
Machine learning
Programming Languages
Python (Computer program language)
Software Engineering
ISBN:9781835464946, 1835464947
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Building accurate machine learning models requires quality data-lots of it. However, for most teams, assembling massive datasets is time-consuming, expensive, or downright impossible. Led by author, a seasoned ML engineer and advocate for surgical data science and climate AI advancements, this hands-on guide to active machine learning demonstrates how to train robust models with just a fraction of the data using Python's powerful active learning tools. You'll master the fundamental techniques of active learning, such as membership query synthesis, stream-based sampling, and pool-based sampling and gain insights for designing and implementing active learning algorithms with query strategy and Human-in-the-Loop frameworks. Exploring various active machine learning techniques, you'll learn how to enhance the performance of computer vision models like image classification, object detection, and semantic segmentation and delve into a machine AL method for selecting the most informative frames for labeling large videos, addressing duplicated data. You'll also assess the effectiveness and efficiency of active machine learning systems through performance evaluation. By the end of the book, you'll be able to enhance your active learning projects by leveraging Python libraries, frameworks, and commonly used tools.
ISBN:9781835464946
1835464947
DOI:10.0000/9781835462683