Machine Learning
284 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
4 lessons
20 practices
3 hours
Model Validation and Selection
Course details
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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