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TensorFlow 2 Beginner

Track :

Programming

Lessons no : 11

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What will you learn in this course?
  • Develop and implement machine learning models using TensorFlow 2's intuitive APIs and eager execution techniques
  • Build, train, and evaluate neural networks for real-world applications with TensorFlow 2 in Google Colab environments
  • Apply TensorFlow 2 for image recognition, classification, and regression tasks with practical, step-by-step guidance
  • Utilize TensorFlow 2's flexible model building tools to create custom deep learning architectures for diverse datasets
  • Optimize machine learning models in TensorFlow 2 for improved accuracy and performance in practical scenarios
  • Leverage TensorFlow 2's high-level APIs to streamline model development and deployment processes
  • Implement transfer learning and fine-tuning techniques within TensorFlow 2 for advanced model customization
  • Troubleshoot and debug TensorFlow 2 models effectively to ensure robust and reliable machine learning solutions

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Lessons | 11


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TensorFlow 2 focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs, and flexible model building on any platform. Many guides are written as Jupyter notebooks and run directly in Google Colab—a hosted notebook environment that requires no setup .