TensorFlow: The best library with optimized implementation for deep learning
June 24, 2019

TensorFlow: The best library with optimized implementation for deep learning

Anonymous | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with TensorFlow

TensorFlow is the best deep learning library for visualization, training and tuning the model with a large dataset. We are using TensorFlow in the research and development department for the training of natural language, image processing and for the application of specific predictive models. It is also used by the production department to support and host the trained models at the application level.
  • Detailed and more functional implementation of various algorithms.
  • Great visualization under TensorFlow board for training models.
  • Multiple GPU support and availability of TPU to train large models.
  • Regular updates.
  • Large user community.
  • Performance issues on a low scale system.
  • Complex to debug for multi GPU training of a large model.
  • It is not easy to use for new developers compared to other libraries.
  • Implementation for complex architecture is difficult.
  • Provides a great predictive capability on a large dataset.
  • Hardware cost for training is a bit concerning for a small organization.
TensorFlow provides a wide range of algorithms with more detail and customization options compared to others. Also, the library is advanced and updates regularly for optimization and new functions.
TensorFlow is well-suited for complex model training with a large dataset using multiple GPU's and provides training time mode visualization for fast debugging of the architecture. If you are doing a proof of concept for new architecture then it would not be a good choice considering implementation complexity and development time.