Software Alternatives & Reviews

MC Stan VS rasa NLU

Compare MC Stan VS rasa NLU and see what are their differences

MC Stan logo MC Stan

Stan is a state-of-the-art platform for statistical modeling and high-performance statistical computation. Thousands of users rely on Stan for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences.

rasa NLU logo rasa NLU

A set of high level APIs for building your own language parser
  • MC Stan Landing page
    Landing page //
    2023-08-18
  • rasa NLU Landing page
    Landing page //
    2023-09-20

MC Stan videos

MC STΔN NUMBERKARI REACTION | MC STAN NUMBERKARI REACTION | MC STAN NEW SONG | TADIPAAR 2K20 | AFAIK

More videos:

  • Review - What is MC STAN ? Is he really worth all the hype? TADIPAAR ALBUM REVIEW | Desi Hip-Hop
  • Review - MC STΔN AMIN REACTION | AMIN REACTION | MC STAN AMIN REACTION | MC STAN REACTION | TADIPAAR | AFAIK

rasa NLU videos

Rasa X Tutorial 1: Constructing a Basic AI Assistant

More videos:

  • Demo - Rasa X Tutorial 2: Expanding Language Understanding

Category Popularity

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Data Science And Machine Learning
Chatbots
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Data Science
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Chatbot Platforms & Tools

User comments

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Social recommendations and mentions

MC Stan might be a bit more popular than rasa NLU. We know about 24 links to it since March 2021 and only 22 links to rasa NLU. 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.

MC Stan mentions (24)

  • [Q] Is there a method for adding random effects to an interval censored time to event model?
    My approach to problems like this is to write down the proposed model mathematically first, in extreme detail. I find hierarchical form to be the easiest way to break it down piece by piece. Once I have the maths then I turn it into a Stan model. Last step is to use the Stan output to answer the research questions. Source: 11 months ago
  • Demand Planning
    For instance my first choice in these cases is always a Bayesian inference tool like Stan. In my experience as someone who’s more of a programmer than mathematician/statistician, Bayesian tools like this make it much easier to not accidentally fool yourself with assumptions, and they can be pretty good at catching statistical mistakes. Source: 12 months ago
  • What do actual ML engineers think of ChatGPT?
    I tend to be most impressed by tools and libraries. The stuff that has most impressed me in my time in ML is stuff like pytorch and Stan, tools that allow expression of a wide variety of statistical (and ML, DL models, if you believe there's a distinction) models and inference from those models. These are the things that have had the largest effect in my own work, not in the sense of just using these tools, but... Source: 12 months ago
  • How to get started learning modern AI?
    Oh its certainly used in practice. You should look into frameworks like Stan[1] and pyro[2]. I think bayesian models are seen as more explainable so they will be used in industries that value that sort of thing [1] https://mc-stan.org/. - Source: Hacker News / about 1 year ago
  • Should I start learning R, SAS, or Python during my gap year?
    At this point the only people using such things are the programmers. Think e.g. STAN. https://mc-stan.org/ the rest of us: R, SAS, Excel. Source: about 1 year ago
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rasa NLU mentions (22)

  • A Dive into Conversational AI
    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
  • Compromising LLM-Integrated Applications with Indirect Prompt Injection
    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
  • ChatGPT Goldmine: Top 5 Money-Making Opportunities You Can't Miss!
    Chatbot frameworks: Utilize chatbot frameworks such as Botpress, Rasa, or Microsoft Bot Framework to streamline development. - Source: dev.to / about 1 year ago
  • How to create an AI model that learns from textbooks and can be asked about the information in them
    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
  • Top 8 AI and Machine Learning Trends to Watch in 2023
    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
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What are some alternatives?

When comparing MC Stan and rasa NLU, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Dialogflow - Conversational UX Platform. (ex API.ai)

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Microsoft Bot Framework - Framework to build and connect intelligent bots.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Wit.ai - Easily create text or voice based bots that humans can chat with on their preferred messaging...