Bunnyshell
Heroku
Porter
Okteto
8base
Flynn
YunoHost
Render UIKit
TensorFlow
PyTorch
Keras
IBM Watson Studio
Scikit-learn
Azure Machine Learning Service
Pega Platform
Azure Machine Learning Studio
Bunnyshell automates all steps in the release process, from creating servers on multiple clouds (AWS, Azure, Google Cloud, Digital Ocean) to easy provisioning (ready to use apps - install & configure with one click) and one click deployments.
We are helping companies save time and money by standardizing and automating otherwise time consuming, knowledge-dependant or prone to error infrastructure-related tasks.
With Bunnyshell and a few clicks, any developer can:
Migrate easily (from premise to cloud, cloud to cloud) Create servers on multiple clouds Provision & configure applications Deploy with one click and zero downtime (multiple deployments time) Version their work and rollback any time Create dev & test environments on any cloud, version, OS Have automated security updates for all projects
Bunnyshell TensorFlowBased on our record, TensorFlow should be more popular than Bunnyshell. It has been mentiond 8 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.
Https://bunnyshell.com and k8s -- seems like a good way to get going quickly with new projects --. - Source: Hacker News / almost 3 years ago
With Infrastructure as Code at its current state of maturity, itโs now easier than ever to replicate microservice environments in the cloud. This unlocked a new approach of having a personal production-like cloud environment for every developer, which they can use freely and in isolation. It comes in two flavors - persistent environments, or ephemeral environments created on demand with products like Okteto or... - Source: dev.to / over 3 years ago
The open-source movement offers hope here. Projects like Hugging Face are democratizing access to state-of-the-art models, while initiatives like Google's TensorFlow provide powerful frameworks without licensing costs. But even open-source solutions require technical expertise that many lack. - Source: dev.to / 4 months 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 3 years 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: about 4 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 4 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: over 4 years ago
Heroku - Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Porter - Heroku that runs in your own cloud
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Okteto - Development platform for Kubernetes applications.
IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.