TensorFlow
PyTorch
Scikit-learn
Keras
OpenCV
IBM Watson Studio
Amazon SageMaker
Pega Platform
Amazon Lex
Dialogflow
IBM Watson Assistant
Microsoft Bot Framework
Botpress
Tars
Chatfuel
rasa NLU
TensorFlow Amazon LexBased on our record, Amazon Lex should be more popular than TensorFlow. It has been mentiond 13 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.
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 / over 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
Amazon's doesn't care about Mturk, they have their own AI that will eventually automate all their work too https://aws.amazon.com/lex/. Source: about 1 year ago
Amazon Lex, AWS's natural language conversational AI service. With Amazon Connect, it seamlessly leverages Amazon Transcribe to understand what is being said (speech-to-text), and Amazon Polly to provide the verbal response (text-to-speech). We aren't really using the Natural Language powers of Lex, but it has other uses for us:. - Source: dev.to / over 1 year ago
AWS has three high-quality tools: Amazon Lex, Amazon Rekognition, and Amazon SageMaker. - Source: dev.to / over 1 year ago
Introducing DTMF slot settings within Amazon Lex.Amazon Lex is a service for building conversational interfaces into any application using voice and text. With Amazon Lex, you can quickly and easily build conversational bots ("chatbots"), virtual agents, and interactive voice response (IVR) systems. Amazon Lex is excited to launch DTMF-only slot settings and configurable session attributes within the Lex console. - Source: dev.to / over 1 year ago
The text processing is a bit more interesting, as we have the original text and some insights into the content and sentiment, but we need a response. So for this application Amazon Lex has been configured to do this. - Source: dev.to / over 1 year ago
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Dialogflow - Conversational UX Platform. (ex API.ai)
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
IBM Watson Assistant - Watson Assistant is an AI assistant for business.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Microsoft Bot Framework - Framework to build and connect intelligent bots.