Rasa-nluWhat is rasa NLU?
rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
rasa NLU is a tool in the Text & Language Models category of a tech stack.
Key Features
Open sourceNLPMachine learning
rasa NLU Pros & Cons
Pros of rasa NLU
- ✓Open Source
- ✓Docker Image
- ✓Self Hosted
- ✓Comes with rasa_core
- ✓Enterprise Ready
Cons of rasa NLU
- ✗No interface provided
- ✗Wdfsdf
rasa NLU Alternatives & Comparisons
What are some alternatives to rasa NLU?
Transformers
It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.
SpaCy
It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
Gensim
It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
