AWS Deep Learning AMIs VS HeidiSQL

AWS Deep Learning AMIs Reviews

HeidiSQL Reviews

1. Mark-Mercer

   | self emloyed dba at Shatz | over 2 years ago
   very good and handy tool

   There was a need to work with the MS SQL database, but I did not want to install and understand the complex SQL Management Studio program, and this product turned out to be very easy to install and use. For more then 2 month i've used the tool haven't came across any issues.

   🏁 Competitors: SQL Server Management Studio

   👍 Pros:    Lightweight|Simple yet powerful and efficient tool|Many built-in features

   👎 Cons:    Nothing, so far

AWS Deep Learning AMIs mentions (3)

• Machine Learning Best Practices for Public Sector Organizations

  AWS Deep Learning AMIs can be used to accelerate deep learning by quickly launching Amazon EC2 instances. - Source: dev.to / over 2 years ago

• Unable to host a Flask App consisting of an Image Classification Model coded in Pytorch to a free tier EC2 instance. The issue occurs at requirements installation i.e The torch v1.8.1 installation gets stuck at 94%.

  Ok a bit more on topic of your question. Set up a docker locally on your computer, pick a relevant image with all the python stuff and then do pip install -r requirements -t ./dependencies zip it up, upload to S3 and then get it from there and use on the EC2 instance. Or look into using Deep Learning AMIs they should have pytorch installed: https://aws.amazon.com/machine-learning/amis/. Source: almost 3 years ago

• Is Sagemaker supposed to replace Keras or PyTorch? Or Tensorflow?

  Literally nothing stops you from running EC2 instance with GPU and configuring it yourself. There are even AMIs specialized for ML workloads with everything preconfigured and ready to use - https://aws.amazon.com/machine-learning/amis/. Source: almost 3 years ago

HeidiSQL mentions (0)