We work with our customers to reimagine the world of business communications and collaboration. This relentless passion to innovate has made us the #1 cloud communications provider worldwide, and we don’t plan on stopping there.
Technology breaks down barriers and unlocks potential, making it easy for people to do their best work together. In today’s mobile world, this means giving teams, partners, and customers the ability to communicate, collaborate, and connect the way they want on any device, anywhere, anytime. It's what we call collaborative communications, and it’s at the heart of everything we do.
With our flexible, cost-effective cloud communications and collaboration solutions, we’ve created the ideal workplace, where business can be done more efficiently and effectively. From an all-in-one cloud phone system with team messaging and video conferencing to a complete contact center and more, we build solutions for every business, no matter how big or small.
Based on our record, TensorFlow should be more popular than RingCentral. It has been mentiond 7 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: about 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
Systems like 8x8/RingCentral/Vonage or even Voip.ms might be ideal for you. Source: over 2 years ago
I saw www.calltrackingmetrics.com ; ringcentral.com ; twilio.com ; Zadarma. At this moment it seems that calltrackingmetrics seems to be the first solution I would try because they put in front of their ads the fact to track with google ads. Twilio seems to be too much complex to use and they don't have an iPhone app ; ringcentral I don't know and Zadarma seems good. Source: about 3 years ago
I use unitelvoice.com. It works fine has an app and can forward to my cell number. Used to use ringcentral.com it was fine when it worked but support was crap. Source: over 3 years ago
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Dialpad - Switch is a cloud-based phone system built for Google Apps users.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Aircall - Aircall is a call center software of a new generation designed for fast growing companies. Setup instantly and integrates to your CRMs
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Nextiva - Business VoIP, cloud phone systems trusted by more than 150,000 companies. Powered by the leading cloud PBX VoIP platform, Nextiva is rated the best business VoIP service provider.