monkeylearn
Amazon Comprehend
spaCy
Google Cloud Natural Language API
BytesView
Chattermill
AYLIEN
Lexalytics Semantria
rasa NLU
Dialogflow
Microsoft Bot Framework
Wit.ai
Botpress
Amazon Lex
Chatfuel
Voiceflow
monkeylearn rasa NLUBased on our record, rasa NLU should be more popular than monkeylearn. It has been mentiond 22 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
MonkeyLearn: A platform for text analysis and machine learning, allowing users to train custom models for tasks like sentiment analysis and topic classification. Source: 5 months ago
Monkeylearn.com — Text analysis with machine learning, free 300 queries/month. - Source: dev.to / over 1 year ago
MonkeyLearn supports 11 languages for data analysis (Spanish, Portuguese, German, Russian, Italian, French, Dutch, Chinese, Japanese, Korean and Arabic). But for sentiment analysis, only Spanish seems to be available, I’m not sure about that. Source: over 1 year ago
R3: Used RedditExtractoR in R to download all-time top posts, and ran the resulting .csv through https://monkeylearn.com/. Downloaded the resulting table and deleted top result "OC" - then visualized it with ggplot to give a sense of absolute numbers. Total posts considered in this are 988, the word cloud only looks at the 98 most mentioned words/phrases. Let me know if you have got any questions/concerns! Source: almost 2 years ago
Go to monkeylearn.com and sign up for a free demo. Then cut and paste your blog text into the extractor/classifier. Source: almost 2 years ago
Beyond raw language models, NLP engines like Rasa and Dialogflow offer frameworks for designing, building, and improving conversational flows. They help in intent recognition, entity extraction, and dialogue management, which are crucial for a coherent conversation structure. - Source: dev.to / about 2 months ago
There are frameworks out there for doing that kind of thing, see https://rasa.com/ for example. It's not using any LLMs at the moment, just BERT and DIET mostly but it's highly customizable and you could likely bring in an LLM for doing some interesting things to handle more complex messages from users. - Source: Hacker News / 12 months ago
Chatbot frameworks: Utilize chatbot frameworks such as Botpress, Rasa, or Microsoft Bot Framework to streamline development. - Source: dev.to / about 1 year ago
Rasa is a popular tool used right now to build these applications. If you're looking for a serious turn-key solution I would check out Vectara. Source: about 1 year ago
Another example is RASA, one of the most popular platforms for creating conversational AI assistants. On the accepted AI quality scale, RASA reaches levels 3 and 4. It means that the "robot" not only understands humans with high accuracy in a given contextual field but also learns to recognize contradictions and ulterior motives. - Source: dev.to / over 1 year ago
Amazon Comprehend - Discover insights and relationships in text
Dialogflow - Conversational UX Platform. (ex API.ai)
spaCy - spaCy is a library for advanced natural language processing in Python and Cython.
Microsoft Bot Framework - Framework to build and connect intelligent bots.
Google Cloud Natural Language API - Natural language API using Google machine learning
Wit.ai - Easily create text or voice based bots that humans can chat with on their preferred messaging...
