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Machine Learning

218 learners

TensorFlow Techniques for Model Optimization

This course delves into advanced TensorFlow techniques to boost model performance and reliability. Learn about using regularization and dropout to prevent overfitting, and explore real-time training improvements with callbacks. Each module is concise and impactful, equipping you with practical skills to enhance your machine learning models.

Python

Scikit-learn

TensorFlow

See path

4 lessons

20 practices

3 hours

Model Validation and Selection

Course details

Implementing L2 Regularization in TensorFlow

Preview

Regularization: See it in Action

Modify Regularization Techniques in Model

Fix the Regularization Mistakes

Add L1 and L2 Regularization

Implement Regularization in TensorFlow

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