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Learn MorePros of MonkeyLearn
Pros of rasa NLU
Pros of SpaCy
Pros of MonkeyLearn
- Easy to use1
Pros of rasa NLU
- Open Source9
- Docker Image6
- Self Hosted6
- Comes with rasa_core3
- Enterprise Ready1
Pros of SpaCy
- Speed12
- No vendor lock-in2
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Cons of MonkeyLearn
Cons of rasa NLU
Cons of SpaCy
Cons of MonkeyLearn
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Cons of rasa NLU
- No interface provided4
- Wdfsdf4
Cons of SpaCy
- Requires creating a training set and managing training1
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What is MonkeyLearn?
Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.
What 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.
What is 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.
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What tools integrate with MonkeyLearn?
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What are some alternatives to MonkeyLearn, rasa NLU, and SpaCy?
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.
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.
Amazon Comprehend
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to discover insights from text. Amazon Comprehend provides Keyphrase Extraction, Sentiment Analysis, Entity Recognition, Topic Modeling, and Language Detection APIs so you can easily integrate natural language processing into your applications.
Google Cloud Natural Language API
You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage on Google Cloud Storage.
Sentence Transformers
It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks.