Data Labeling in Machine Learning with Python

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Discover data labeling methods through Python libraries, ML algorithms, and generative AI with this guide covering best practices, advanced methods, and tools. This course will simplify model training for regression, classification, and clustering. This resource equips learners with the essential skills to label and analyze diverse data types using Python, empowering them to build intelligent systems and extract meaningful insights from raw data. It covers practical techniques for data exploration, annotation, and enhancement, making it a valuable tool for anyone looking to advance their machine learning capabilities. This resource is ideal for machine learning engineers, data scientists, and Python developers looking to expand their data labeling and analysis skills. Basic Python knowledge is helpful but not required. Learners will gain practical expertise in labeling and enhancing data for machine learning models. This course starts with the introduction of exploratory data analysis using Python libraries and then covers the data labeling for tabular data, text data, image data, audio data using heuristics, semi-supervised learning, unsupervised learning and data augmentation. Finally, this course also delves into best practices and tools in the industry for data labeling. This course is based on Data Labeling in Machine Learning with Python, by Vijaya Kumar Suda. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

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