LinkedIn – Hands-On Data Annotation: Applied Machine Learning 2023-12

In Hands-On Data Annotation: Applied Machine Learning, Woraula Oyewosi delves deeply into the intricacies of data annotation for machine learning. He shows how data is prepared and used to train machine learning models. Oyewosi begins with an overview of the principles, types, and importance of data annotation in machine learning pipelines. He then explores practical use cases for data annotation in natural language processing, computer vision, and general data science using a variety of tools. Other topics include the use of open-source and proprietary tools for data annotation, as well as data labeling on major cloud platforms such as AWS, Azure, and GCP.

What you will learn

• In this course, learners will learn how to prepare and use data to train machine learning models. They will understand the principles, types, and importance of data annotation in machine learning processes.
• This course helps participants gain practical skills in data annotation for various applications including natural language processing, computer vision, and data science.
• They will also learn how to use a variety of tools, both open source and proprietary, to annotate data. Additionally, learners will learn how to label data on leading cloud platforms such as AWS, Azure, and GCP.

This course is suitable for people who:

• This course is designed for those curious about how data powers machine learning and data science. It is also ideal for those looking to gain practical skills in data annotation for machine learning applications.
• Students, data engineers, data scientists, machine learning professionals, and anyone interested in a deeper understanding of the role of data in AI can benefit from this course. This course is especially recommended for those who plan to participate in machine learning projects and need a comprehensive understanding of the data preparation and labeling process.

Hands-On Data Annotation: Applied Machine Learning Course Details

• Publisher: LinkedIn
• Instructor: Wuraola Oyewusi
• Training level: Beginner to advanced
• Training duration: 3 hours and 51 minutes

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Sample course video

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502 MB