midTensorFlow
What is the difference between TensorFlow 1.x and 2.x?
Updated May 16, 2026
Short answer
TF2 introduces eager execution, simplified APIs, and Keras integration.
Deep explanation
TF1 relied on static graphs and sessions, while TF2 emphasizes simplicity, eager execution, and high-level APIs like tf.keras.
Real-world example
Modern deep learning models use TensorFlow 2.x.
Common mistakes
- Using TF1 session-based code in TF2.
Follow-up questions
- Is TF1 still used?