Based on our record, PyTorch seems to be a lot more popular than Microsoft Bot Framework. While we know about 106 links to PyTorch, we've tracked only 5 mentions of Microsoft Bot Framework. 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.
Chatbot frameworks: Utilize chatbot frameworks such as Botpress, Rasa, or Microsoft Bot Framework to streamline development. - Source: dev.to / about 1 year ago
I have developed MS Teams Message Extension using Java[Spring Boot] and registered the bot in Botframework Development portal[https://dev.botframework.com/]. It is working fine in local. I tested in local environment using a tunneling application named localtunnel. I tested the extension in MS Teams. Source: about 2 years ago
Maybe this will fit your needs? Microsoft Bot Framework - https://dev.botframework.com/. Source: over 2 years ago
This library (also Node.Js) lets you connect to The Microsoft Bot Framework. Source: over 2 years ago
Besides building informational chatbots using QnA Maker, Azure also provides a larger Bot Service for developing more sophisticated chatbots. Transactional chatbots perform operations such as accessing and modifying internal IT documents and databases and dynamic and context aware chatbots can be used as virtual assistants. Bot Framework is an SDK that lets developers create these kinds of chatbots using their... - Source: dev.to / almost 3 years ago
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more... - Source: dev.to / 27 days ago
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / 2 months ago
Import torch # we use PyTorch: https://pytorch.org Data = torch.tensor(encode(text), dtype=torch.long) Print(data.shape, data.dtype) Print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this. - Source: dev.to / 3 months ago
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries. - Source: dev.to / 2 months ago
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework. - Source: dev.to / 2 months ago
Botpress - Open-source platform for developers to build high-quality digital assistants
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)
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Amazon Lex - Harness the power behind Amazon Alexa for your own conversational apps.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.