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Amazon SageMaker VS Tabler

Compare Amazon SageMaker VS Tabler 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.

Tabler logo Tabler

Admin panel made simple
  • Amazon SageMaker Landing page
    Landing page //
    2023-03-15
  • Tabler Landing page
    Landing page //
    2023-03-15

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)

Tabler videos

No Tabler videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Amazon SageMaker and Tabler)
Data Science And Machine Learning
Productivity
0 0%
100% 100
AI
100 100%
0% 0
Developer Tools
0 0%
100% 100

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 Tabler

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

Tabler Reviews

We have no reviews of Tabler yet.
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Social recommendations and mentions

Based on our record, Amazon SageMaker should be more popular than Tabler. It has been mentiond 37 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 (37)

  • Quantum Convolutional Neural Networks
    Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. - Source: dev.to / 22 days ago
  • Observations on MLOps–A Fragmented Mosaic of Mismatched Expectations
    Damn straight. Oh, wait, some vendors have claimed to build an end-to-end solution. But, meh, that’s marketing talk. Take, for example, a well-known platform like Amazon Sagemaker, which describes itself as “a fully managed service that brings together a broad set of tools to enable high-performance, low-cost machine learning (ML) for any use case.” It’s a great platform. My startup has even partnered with them.... - Source: dev.to / about 2 months ago
  • 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 / 3 months 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 / 5 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: about 1 year ago
View more

Tabler mentions (14)

  • What css library to use?
    [SELF PROMO] also we have made a library called YeSvelte which supports tabler.io and daisyui themes. Source: about 1 year ago
  • Show HN: Tremor 3.0 – The open-source library to build dashboards fast
    This is nice. For more choices, if you are looking, Tabler[1] is another such component template, and I have used it to knock off visual dashboards fast. Not related; just another happy user. 1. https://tabler.io. - Source: Hacker News / about 1 year ago
  • We have started a new Svelte component library inspired by tabler.io: YeSvelte
    YeSvelte is a powerful and flexible Svelte UI component library, designed to help developers build enterprise-grade web applications quickly and easily. With a focus on rapid application development and framework independence, YeSvelte is the perfect complement to any CSS framework. It is inspired by Tabler, a UI Kit built on top of Bootstrap css. Source: over 1 year ago
  • We have started a new Svelte component library inspired by tabler.io: YeSvelte
    Also, we have developed a wrapper CSS on top of tabler.io and Bootstrap. Developers have access to the classes if they want to use them. Source: over 1 year ago
  • Using Pre-made html Template
    Looks like your issue is resolved. I can also recommend having a look at tabler.io. I use it for most of my flask apps and its very simple/nice for dashboard UI's. Hope you find it useful :). Source: over 1 year ago
View more

What are some alternatives?

When comparing Amazon SageMaker and Tabler, 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.

Blur Admin - Angular admin panel front-end framework

Deepnote - A collaboration platform for data scientists

Jet Admin - Build business apps really fast

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.

Forest Admin - Execute fast and at scale with no time wasted on internal tools developed in-house.