rasa NLU
Dialogflow
Microsoft Bot Framework
Wit.ai
Botpress
Amazon Lex
Chatfuel
Voiceflow
NumPy
Pandas
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
rasa NLUBased on our record, NumPy should be more popular than rasa NLU. It has been mentiond 107 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.
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 / 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: over 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
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 7 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
Dialogflow - Conversational UX Platform. (ex API.ai)
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Microsoft Bot Framework - Framework to build and connect intelligent bots.
OpenCV - OpenCV is the world's biggest computer vision library
Wit.ai - Easily create text or voice based bots that humans can chat with on their preferred messaging...
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
