Amazon Lex Reviews

Keras Reviews

Amazon Lex mentions (14)

• Exploring Use Cases for Cognitive Services

  However, APIs like Watson Assistant or Amazon Lex make it easy to build services that can apply logic to observed patterns in those natural-language requests. These services may, for instance, observe a sudden rush of calls from an airport suffering take-off delays and change the sequence of options to prioritize rescheduling flights. Or they may see that calls from a particular country or region tend to be... - Source: dev.to / 14 days ago

• Chances of Amazon Turk shutting down in the future?

  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

• GPT-Powered chatbot over the phone - Try it, and see how it was built

  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

• How AWS and GCP Compare: The Top 5 Differences

  AWS has three high-quality tools: Amazon Lex, Amazon Rekognition, and Amazon SageMaker. - Source: dev.to / over 1 year ago

• AWS NLP newsletter November 2022

  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

Keras mentions (32)

• Using Google Magika to build an AI-powered file type detector

  The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 4 days ago

• My Favorite DevTools to Build AI/ML Applications!

  As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 2 months ago

• Getting Started with Gemma Models

  After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / about 2 months ago

• How popular are libraries in each technology

  Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / 12 months ago

• Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!

  I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago