Leading framework with NCE loss and word embeddings support for NLP tasks.
TensorFlow
GPU-accelerated framework with automatic differentiation for NLP.
PyTorch
Python library for defining and evaluating mathematical expressions, used in NLP.
Theano
Simple API integrated with TensorFlow for visual question-answering models.
Keras
Python-based framework for flexible deep learning, including RNNLM.
Chainer
Integrated toolkit with linguistic analysis tools for NLP.
Stanford CoreNLP
Transparent deep learning library with high-level APIs for TensorFlow.
TFLearn
TensorFlow, Keras, and PyTorch dominate the NLP community, while other alternatives offer unique advantages and collaborate for a better overall experience.
Framework Adoption
With a vast collection of methods, TensorFlow's popularity stems from its ability to make machines understand human language effectively.
TensorFlow's Strengths
The wide adoption of NLP applications by top companies has turned NLP skills into a hot commodity in the job market.