7 Popular NLP Frameworks in Machine Learning

Leading framework with NCE loss and word embeddings support for NLP tasks.


GPU-accelerated framework with automatic differentiation for NLP.


Python library for defining and evaluating mathematical expressions, used in NLP.


Simple API integrated with TensorFlow for visual question-answering models.


Python-based framework for flexible deep learning, including RNNLM.


Integrated toolkit with linguistic analysis tools for NLP.

Stanford CoreNLP

Transparent deep learning library with high-level APIs for TensorFlow.


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.

NLP in High Demand

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