Do you like Tensorflow for building applications? If so, you might have already learned how to install and configure it on your local environment to test things out. Next, you’ll need Tensorflow friendly hosting. If you’re just starting out, free hosting probably sounds pretty good. When your site or app needs grow, however, free plans probably won’t cut it. We’ve put together a list of the best Tensorflow hosting providers to help you make the right choice. Below, you’ll find a brief review of each service, plus the pros and cons.
Azure is a comprehensive set of cloud services that developers and IT professionals use to build, deploy, and manage applications through our global network of datacenters. Integrated tools, DevOps, and a marketplace support you in efficiently building anything from simple mobile apps to internet-scale solutions.
- URL: https://azure.microsoft.com/
TensorFlow™ enables developers to quickly and easily get started with deep learning in the cloud. The framework has broad support in the industry and has become a popular choice for deep learning research and application development, particularly in areas such as computer vision, natural language understanding and speech translation. You can get started using TensorFlow on AWS by launching the AWS Deep Learning AMI which comes bundled with TensorFlow, as well as other popular deep learning frameworks such as Apache MXNet and Gluon, Caffe, Caffe2, Theano, Torch, Keras, and the Microsoft Cognitive Toolkit.
- URL: https://aws.amazon.com/tensorflow/
Bitnami is a rapidly growing, self-funded, profitable and globally distributed company. To maintain our singular focus on being leaders in application packaging our decision making is guided by the Bitnami values, which continually challenge us to engineer simple solutions to the ever-changing complex problems that our users face, and to work collaboratively through that process.
- URL: https://bitnami.com/
Heroku is a cloud platform that lets companies build, deliver, monitor and scale apps — we’re the fastest way to go from idea to URL, bypassing all those infrastructure headaches. “There’s an app for that” – only a few years ago a catchy marketing campaign introduced the world to a new relationship with the mobile phone. Now, apps have become a way of life for most of us. Whether mobile or web, apps and their underlying APIs are how we manage our lives, make purchases, socialize, stay informed, and interact with customers.
- URL: https://www.heroku.com/
Google Cloud Machine Learning Engine is a managed service that enables you to easily build machine learning models that work on any type of data, of any size. Create your model with the powerful TensorFlow framework that powers many Google products, from Google Photos to Google Cloud Speech. Cloud Machine Learning Engine can take any TensorFlow model and perform large scale training on a managed cluster.
- URL: https://cloud.google.com/
Defined in tensorflow/_api/v1/app/__init__.py.. Generic entry point script. Modules. flags module: Import router for absl.flags. See https://github.com/abseil/abseil Loading TensorFlow graphs from Node.js. create a new folder for the host language. many TensorFlow functions return a TF_Status struct and checking the status can get tedious. Hosting TensorFlow using Docker on Alibaba Cloud TensorFlow is an open source library for numerical computation, specializing in machine learning applications. In this tutorial, you will learn how to install and run TensorFlow on a single machine, and will train a simple classifier to classify images of flowers. Where can I host a tensorflow project? Update Cancel. Answer Wiki. 2 Answers. Waleed Kadous, Alternatively, you could always host on AWS, with or without GPUs. This would require you to set up and AMI specifically with TensorFlow on it and then deploy it. What’s a good hosting option for a small side-project? Ask New Question. GitHub is home to over 28 million developers working together to host and review code, manage projects, and build software together. Sign up. TF detect app crash Getting crash #6022. Open M1thun opened this Issue Jan 10, 2019 · 2 comments python -c “import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)” Describe the problem. Join GitHub today. GitHub is home to over 28 million developers working together to host and review code, manage projects, and build software together. In simple terms, the job of tf.app.run() is to first set the global flags for later usage like: from tensorflow.python.platform import flags f = flags.FLAGS and then run your custom main function with a set of arguments.