From the course: Building and Deploying Deep Learning Applications with TensorFlow
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Hardware, software, and language requirements - TensorFlow Tutorial
From the course: Building and Deploying Deep Learning Applications with TensorFlow
Hardware, software, and language requirements
- [Instructor] Let's talk about the tangibles you need to get started. TensorFlow has different hardware and software requirements for the development phase and the runtime phase. The Development phase is when you are first coding and then training a neural network. This is usually done on your own computer. The Runtime phase, also called the inference phase, is when you are using a trained neural network to make predictions. This might be done on your own computer, on a cloud server, or on a user's computer, or mobile device. When you are developing machine learning models with TensorFlow, you need a computer running Windows, macOS, or Linux. For very large projects you might take advantage of multiple Linux computers in the cloud to speed up processing. But once you have a trained model you can run it on a wider range of computers and hardware devices. You can run your trained models on Mac, Windows, and Linux desktops, as a web service on Linux servers using the TensorFlow Serving…
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