rasa NLU
Dialogflow
Microsoft Bot Framework
Botpress
Wit.ai
Amazon Lex
Chatfuel
spaCy
TensorFlow
PyTorch
Scikit-learn
Keras
IBM Watson Studio
OpenCV
Amazon SageMaker
Pega Platform
rasa NLU| Categories |
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|---|---|
| Website | rasa.com |
| Pricing URL | Official rasa NLU Pricing |
| Details $ |
TensorFlow| Categories |
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| Website | tensorflow.org |
| Pricing URL | - |
| Details $ |
Based on our record, rasa NLU should be more popular than TensorFlow. 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.
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 1 month 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 / 11 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
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / about 1 year ago
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 2 years ago
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: almost 2 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 2 years ago
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 2 years ago
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.
Botpress - Open-source platform for developers to build high-quality digital assistants
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
