https://github.com/dipanjans/deep-learning-cloud-gpu-setup-guide

Learn how to start using deep learning frameworks leveraging python, jupyter notebooks in the cloud using GPUs with a ready-reference guide
https://github.com/dipanjans/deep-learning-cloud-gpu-setup-guide

Last synced: 13 days ago
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Learn how to start using deep learning frameworks leveraging python, jupyter notebooks in the cloud using GPUs with a ready-reference guide

• Host: GitHub
• URL: https://github.com/dipanjans/deep-learning-cloud-gpu-setup-guide
• Owner: dipanjanS
• License: apache-2.0
• Created: 2017-10-28T09:15:22.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2017-10-28T09:33:27.000Z (over 7 years ago)
• Last Synced: 2024-12-15T17:45:02.111Z (2 months ago)
• Size: 6.84 KB
• Stars: 1
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# Setup a Cloud based Deep Learning Environment leveraging GPUs

In this guide, we will look at a structured tutorial towards setting up a cloud based deep learning enviroment with GPU computing enabled. The idea is to enable you with a deep learning environment which can be accessed from anywhere thanks to the cloud and also help you rapidly prototype deep learning models thanks to the power of GPU based computing. Of course you can always build your models using CPU here too but the idea is to speed-up training times using GPU especially for resource hogging models like RNNs and LSTMs.




## Requirements

✔ An [Amazon AWS account](https://aws.amazon.com)


✔ Some 💲 for paying compute\storage charges


✔ A bit of your precious time 😉





# Step 1: Setup your Deep Learning Instance