AWS IoT Core might be a bit more popular than TensorFlow. We know about 8 links to it since March 2021 and only 7 links to TensorFlow. 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.
MQTT - AWS IoT Core offers a managed MQTT message broker, giving you easy access to your devices. Fun fact, this is what powers the notifications in Serverlesspresso. - Source: dev.to / 7 months ago
AWS IoT: For real-time communication between the server and the frontend application. - Source: dev.to / about 1 year ago
AWS IoT Core is a service that allows you to connect your devices securely to the AWS cloud and with ease. Option for device management, data processing as well as integration with other AWS services is provided. Click here for more on AWS IoT Core. - Source: dev.to / about 1 year ago
From here you can do all sorts of actions. For example, the serverless-coffee project used IOT Core. With IOT Core you can notify the end-user with status updates. And notify the barista that what kind of coffee needs to be created. - Source: dev.to / about 1 year ago
When you need websockets in a project on AWS most likely API Gateway Websockets (I will refer to it as API Gateway from now on) is the first service coming to mind. At some point when looking into options, I ran into IoT Core instead. I thought this was meant only for very specific scenarios involving hardware; however it also supports MQTT over websockets which makes it an amazing choice for web and app. I think... - 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 / 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
AWS IoT - Easily and securely connect devices to the cloud.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
ThingSpeak - Open source data platform for the Internet of Things. ThingSpeak Features
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Particle.io - Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.