Book Image

Data Labeling in Machine Learning with Python

By : Vijaya Kumar Suda
Book Image

Data Labeling in Machine Learning with Python

By: Vijaya Kumar Suda

Overview of this book

Data labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today’s data-driven world, mastering data labeling is not just an advantage, it’s a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you’ll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.
Table of Contents (18 chapters)
1
Part 1: Labeling Tabular Data
5
Part 2: Labeling Image Data
9
Part 3: Labeling Text, Audio, and Video Data

Part 1: Labeling Tabular Data

This part of the book will guide you in exploring tabular data and programmatically labeling the data using Python libraries, such as Snorkel labeling functions. You will be able to achieve this without requiring any prior data science knowledge. Additionally, it covers data labeling using K-means clustering.

This part comprises the following chapters: