Description
Data Labeling for Machine Learning course. Roughly 2.5 quintillion bytes of data are generated every day—mostly raw, unlabeled data—but supervised learning techniques for machine learning require labeling the data in order to use it for training. This makes data labeling time-consuming and expensive, but a vital part of machine learning. In this course, Google Cloud Architect and Certified Data Engineer Janani Ravi walks you through how to get started with data tagging. Learn about different approaches to data labeling, as well as challenges, best practices, and use cases. Jump into data labeling with Azure ML and learn how to set up an image labeling project and perform manual image labeling, review, and review progress. Walk through the steps to perform manual and ML-assisted data labeling in Azure, then explore how to use Snorkel to label data, including how to create various labeling models and functions. This course is created by Janani Ravi. We are happy to host this training in our library.
What you will learn in the Data Labeling for Machine Learning course
- Data labeling process
- Data labeling approaches
- Data labeling challenges, best practices and use cases
- Data labeling with Azure ML
- Set up an Azure ML workspace
- Launching an image tagging project: creating data assets
- Labeling and manual image review
- Check the progress of manual labeling
- Configure inference for new training runs
- Explore labeled datasets
- Examining the educational criteria of the model
- Automatic machine learning for image classification
- Programmatic Tagging with Snorkel
- Programmatic tagging using the majority tag voter
Data Labeling for Machine Learning course specifications
- Publisher: LinkedIn
- teacher: Janani Ravi
- Training level: beginner
- Training duration: 1 hour and 54 minutes
The headings of the Data Labeling for Machine Learning course
Course images
Sample video of the course
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
File(s) password: www.downloadly.ir
Size
250 MB
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