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TensorFlow Techniques for Model Optimization

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Overview

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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.

Syllabus

  • Lesson 1: Implementing L2 Regularization in TensorFlow
  • Lesson 2: Adding Dropout to Prevent Overfitting
  • Lesson 3: Utilizing Callbacks in TensorFlow
  • Lesson 4: Bridging TensorFlow and Scikit-Learn through Keras Wrappers

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