Offered By: IBMSkillsNetwork
Autoencoders and Regularization - Learn and Implement
In this course, you'll explore how Autoencoders compress, denoise, and derive valuable features from data. You'll also delve into regularization to curb overfitting and boost model generalizability. Autoencoders play roles in image enhancement, anomaly spotting, recommendation engines, and generative modelling. Meanwhile, regularization is essential in nearly every machine-learning endeavor. This training will equip you to address practical challenges across various applications.
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Artificial Intelligence
126 EnrolledAt a Glance
In this course, you'll explore how Autoencoders compress, denoise, and derive valuable features from data. You'll also delve into regularization to curb overfitting and boost model generalizability. Autoencoders play roles in image enhancement, anomaly spotting, recommendation engines, and generative modelling. Meanwhile, regularization is essential in nearly every machine-learning endeavor. This training will equip you to address practical challenges across various applications.
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Course Syllabus
- Regularization
- Autoencoders
- Variational Autoencoders