Software Alternatives & Reviews

3D semantic segmentation by Playment VS Amazon SageMaker

Compare 3D semantic segmentation by Playment VS Amazon SageMaker and see what are their differences

3D semantic segmentation by Playment logo 3D semantic segmentation by Playment

Accurate 3D point cloud segmentation to train your AI models

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.
  • 3D semantic segmentation by Playment Landing page
    Landing page //
    2023-07-03
  • Amazon SageMaker Landing page
    Landing page //
    2023-03-15

3D semantic segmentation by Playment videos

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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)

Category Popularity

0-100% (relative to 3D semantic segmentation by Playment and Amazon SageMaker)
AI
16 16%
84% 84
Data Science And Machine Learning
Developer Tools
100 100%
0% 0
Machine Learning
0 0%
100% 100

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Reviews

These are some of the external sources and on-site user reviews we've used to compare 3D semantic segmentation by Playment and Amazon SageMaker

3D semantic segmentation by Playment Reviews

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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

Social recommendations and mentions

Based on our record, Amazon SageMaker seems to be more popular. 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.

3D semantic segmentation by Playment mentions (0)

We have not tracked any mentions of 3D semantic segmentation by Playment yet. Tracking of 3D semantic segmentation by Playment recommendations started around Mar 2021.

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 / 21 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: almost 1 year 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
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What are some alternatives?

When comparing 3D semantic segmentation by Playment and Amazon SageMaker, you can also consider the following products

Apple Core ML - Integrate a broad variety of ML model types into your app

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.

ML5.js - Friendly machine learning for the web

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.

Amazon Machine Learning - Machine learning made easy for developers of any skill level

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