- Course
Efficient Data Feeding and Labeling for Model Training
Creating data models using machine learning requires effective training data. This course will teach you how to feed your data model’s training process using data labeling for supervised training and unlabeled data for semi-supervised training.
Beginner
- Course
Efficient Data Feeding and Labeling for Model Training
Creating data models using machine learning requires effective training data. This course will teach you how to feed your data model’s training process using data labeling for supervised training and unlabeled data for semi-supervised training.
Beginner
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This course is included in the libraries shown below:
- AI
- Data
What you'll learn
Machine learning data models are only as effective as their training data. In this course, Efficient Data Feeding and Labeling for Model Training, you’ll gain the ability to finalize the preparation of your training data and choose the most appropriate manner to feed it into your data model training. First, you’ll explore the meaning of data feeding and common techniques. Next, you’ll discover data labeling for supervised learning, followed by unlabeled data for semi-supervised learning. Finally, you’ll learn how to employ data labeling tools.
When you’re finished with this course, you’ll have the skills and knowledge of data labeling and feeding needed to train machine learning data models.
Efficient Data Feeding and Labeling for Model Training
Beginner
Table of contents
Author of a best-selling mobile app book using Xamarin, Dan Hermes is a Xamarin MVP, Microsoft Regional Director and MVP, IBM Champion, and founder of Lexicon Systems. Mr. Hermes helps developers create great mobile apps and, leveraging IoT and AI, helps businesses develop a winning mobile strategy.