Software Alternatives & Reviews

AWS Deep Learning AMIs VS Amazon Machine Learning

Compare AWS Deep Learning AMIs VS Amazon Machine Learning and see what are their differences

AWS Deep Learning AMIs logo AWS Deep Learning AMIs

The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at any scale.

Amazon Machine Learning logo Amazon Machine Learning

Machine learning made easy for developers of any skill level
  • AWS Deep Learning AMIs Landing page
    Landing page //
    2023-04-30
  • Amazon Machine Learning Landing page
    Landing page //
    2023-03-13

AWS Deep Learning AMIs videos

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Amazon Machine Learning videos

Introduction to Amazon Machine Learning - Predictive Analytics on AWS

More videos:

  • Tutorial - AWS Machine Learning Tutorial | Amazon Machine Learning | AWS Training | Edureka

Category Popularity

0-100% (relative to AWS Deep Learning AMIs and Amazon Machine Learning)
Diagnostics Software
100 100%
0% 0
AI
0 0%
100% 100
Development
100 100%
0% 0
Data Science And Machine Learning

User comments

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Social recommendations and mentions

Based on our record, AWS Deep Learning AMIs should be more popular than Amazon Machine Learning. It has been mentiond 3 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.

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

Amazon Machine Learning mentions (2)

  • Rant + Planning to learn full stack development
    There’s also the ML as a service (MLaaS) movement that lowers the barrier for common ML capabilities (eg image object detection and audio transcription). Basically, you use APIs. See: https://aws.amazon.com/machine-learning/. Source: over 1 year ago
  • Ask the Experts: AWS Data Science and ML Experts - Mar 9th @ 8AM ET / 1PM GMT!
    Do you have questions about Data Science and ML on AWS - https://aws.amazon.com/machine-learning/. Source: about 3 years ago

What are some alternatives?

When comparing AWS Deep Learning AMIs and Amazon Machine Learning, you can also consider the following products

AWS Auto Scaling - Learn how AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost.

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

IBM Cloud Bare Metal Servers - IBM Cloud Bare Metal Servers is a single-tenant server management service that provides dedicated servers with maximum performance.

Lobe - Visual tool for building custom deep learning models

Faronics Deep Freeze - Faronics Deep Freeze provides the ultimate workstation protection by preserving the desired computer configuration and settings.

Apple Machine Learning Journal - A blog written by Apple engineers