EffectiveTensorflow
This comprehensive guide examines TensorFlow 2, focusing on its user-friendly API and resemblance to NumPy. It covers efficient computation strategies, symbolic and iterative methods, and control flow operations such as conditionals and loops. The guide also addresses debugging when using broadcasting and using overloaded operators for clearer code. In addition, it discusses prototyping with Python operations and advanced visualization. The emphasis is on numerical stability to aid the development of robust AI models, with updates tracking the latest TensorFlow API releases.
