Software Alternatives & Reviews

Amazon SageMaker VS Azure Machine Learning Service

Compare Amazon SageMaker VS Azure Machine Learning Service and see what are their differences

Amazon SageMaker logo Amazon SageMaker

Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.

Azure Machine Learning Service logo Azure Machine Learning Service

Build and deploy machine learning models in a simplified way with Azure Machine Learning service. Make machine learning more accessible with automated capabilities.
  • Amazon SageMaker Landing page
    Landing page //
    2023-03-15
  • Azure Machine Learning Service Landing page
    Landing page //
    2023-07-22

Amazon SageMaker

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Machine Learning
  • AI
Website aws.amazon.com
Pricing URL-

Azure Machine Learning Service

Categories
  • Machine Learning
  • AI
  • Data Science And Machine Learning
  • Data Science Tools
Website azure.microsoft.com
Pricing URL Official Azure Machine Learning Service Pricing

Amazon SageMaker videos

Build, Train and Deploy Machine Learning Models on AWS with Amazon SageMaker - AWS Online Tech Talks

More videos:

  • Review - An overview of Amazon SageMaker (November 2017)

Azure Machine Learning Service videos

What is Azure Machine Learning service and how data scientists use it

More videos:

  • Review - Azure Machine Learning service: Part 2 Training a Model

Category Popularity

0-100% (relative to Amazon SageMaker and Azure Machine Learning Service)
Data Science And Machine Learning
AI
59 59%
41% 41
Data Science Tools
0 0%
100% 100
Machine Learning
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Amazon SageMaker and Azure Machine Learning Service

Amazon SageMaker Reviews

7 best Colab alternatives in 2023
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning. It allows users to write code, track experiments, visualize data, and perform debugging and monitoring all within a single, integrated visual interface, making the process of developing, testing, and deploying models much more manageable.
Source: deepnote.com

Azure Machine Learning Service Reviews

The 16 Best Data Science and Machine Learning Platforms for 2021
Description: The Azure Machine Learning service lets developers and data scientists build, train, and deploy machine learning models. The product features productivity for all skill levels via a code-first and drag-and-drop designer, and automated machine learning. It also features expansive MLops capabilities that integrate with existing DevOps processes. The service touts...

Social recommendations and mentions

Based on our record, Amazon SageMaker should be more popular than Azure Machine Learning Service. It has been mentiond 35 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.

Amazon SageMaker mentions (35)

  • Sentiment Analysis with PubNub Functions and HuggingFace
    At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides... - Source: dev.to / 15 days ago
  • Beginning the Journey into ML, AI and GenAI on AWS
    Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 3 months ago
  • Technical Architecture for LLMOps
    Amazon and Azure already have much of what you're talking about in AWS SageMaker and Azure MLOps. Source: 11 months ago
  • Are AI fine-tuning tools worth learning and investing?
    And there have been several platforms that help fine-tune pretrained models, such as Google Cloud AutoML and Amazon Sagemaker. These tools are often fairly easy to use, but they come at a cost. They can be expensive, depending on the size of your dataset. Another option is Finetuner+, that also fine-tunes like AutoML and Sagemaker. The big advantage is that you don't need to transfer your data to other GPUs,... Source: 12 months ago
  • Live object recognition system using Kinesis and SageMaker
    In this blog, you will see how to ingest audio/video feeds from any live recording camera into the AWS Kinesis Video Stream and apply various machine learning algorithms on the video stream to analyze these video feeds using Amazon SageMaker. We'll also use a few other services like Lambda, S3, EC2, IAM, ECS, CloudFormation, ECR, CloudWatch, etc. To power our model. Source: about 1 year ago
View more

Azure Machine Learning Service mentions (4)

  • AI Team Collaboration with Azure ML Studio
    Building an AI solution requires more than just one person. You need a team of experts who can work together efficiently and creatively. That’s why you need a platform that supports collaboration and communication among your AI team members. Azure Machine Learning Studio is not only a powerful infrastructure for computation and technical tasks, but also a management tool that helps you organize and streamline your... - Source: dev.to / 9 months ago
  • Databricks 2022 vs Databricks 2025
    I'm biased, but giving my honest personal opinion here, I think this sounds like a bad idea. I'm not optimistic about Databricks long term. They are a data prep company masquerading as a data science company. Nothing wrong with that, but Spark resources are expensive compared with SQL, and they are at risk from all fronts (Cloud providers, Snowflake, AI/ML platform players, etc.). I see their Databricks controlled... Source: about 2 years ago
  • 20+ Free Tools & Resources for Machine Learning
    Azure Machine Learning An enterprise-grade service for the end-to-end machine learning life cycle that allows you to build models at scale. - Source: dev.to / about 2 years ago
  • Jobs which combine Chemical Engineering and Computer Science
    Azure Machine Learning (specifically for Energy and Manufacturing. Source: about 3 years ago

What are some alternatives?

When comparing Amazon SageMaker and Azure Machine Learning Service, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Azure Machine Learning Studio - Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.

Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.