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Amazon Machine Learning VS Deepnote

Compare Amazon Machine Learning VS Deepnote and see what are their differences

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Amazon Machine Learning logo Amazon Machine Learning

Machine learning made easy for developers of any skill level

Deepnote logo Deepnote

A collaboration platform for data scientists
  • Amazon Machine Learning Landing page
    Landing page //
    2023-03-13
  • Deepnote Landing page
    Landing page //
    2023-10-09

Amazon Machine Learning videos

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Introduction to Amazon Machine Learning - Predictive Analytics on AWS

More videos:

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

Deepnote videos

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Could this be the Best Data Science Notebook? (Deepnote)

Category Popularity

0-100% (relative to Amazon Machine Learning and Deepnote)

Amazon Machine Learning

Deepnote

AI
74 74%
AI
26% 26
Data Science And Machine Learning
51 51%
Data Science And Machine Learning
49% 49
Developer Tools
72 72%
Developer Tools
28% 28
Productivity
0 0%
Productivity
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 Machine Learning and Deepnote

Amazon Machine Learning Reviews

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Deepnote Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Deepnote is a cloud-based data science notebook platform comparable to Jupyter Notebooks but with a focus on real-time collaboration and editing. It lets users write and run code in several programming languages, as well as include text, equations, and visualizations in a single document.
Source: lakefs.io
7 best Colab alternatives in 2023
Deepnote is a real-time collaborative notebook. It offers features like real-time collaboration, version control, and smart autocomplete. It also provides direct integrations with popular data sources like GitHub, Google Drive, and BigQuery. Its modern, intuitive interface makes it a compelling choice for both beginners and experienced data scientists.
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Deepnote is a cloud-based, data science notebook platform that is similar to Jupyter Notebooks, but with a focus on collaboration and real-time editing. It allows users to write and execute code in a variety of programming languages, as well as include text, equations, and visualizations in a single document. Deepnote also has a built-in code editor and supports a wide range...
Source: noteable.io
The Best ML Notebooks And Infrastructure Tools For Data Scientists
A Jupyter-notebook enabled platform, Deepnote boasts of many advanced features. Deepnote supports real-time collaboration to discuss and debug the code. The platform will soon have functions such as versioning, code review, and reproducibility. Deepnote has intelligent features to quickly browse the code, find patterns in your data, and autocomplete code. It can integrate...
Source: analyticsindiamag.com

Social recommendations and mentions

Based on our record, Deepnote seems to be a lot more popular than Amazon Machine Learning. While we know about 32 links to Deepnote, we've tracked only 2 mentions of Amazon Machine Learning. 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 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

Deepnote mentions (32)

  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Deepnote - A new data science notebook. Jupyter is compatible with real-time collaboration and running in the cloud. The free tier includes unlimited personal projects, up to 750 hours of standard hardware, and teams with up to 3 editors. - Source: dev.to / 3 months ago
  • JupyterLab 4.0
    We looked into many of these issues with Deepnote (YC S19) [https://deepnote.com/]. What we found is that these are not necessarily problems of the underlying medium (a notebook), but more of the specific implementation (Jupyter). We've seen a lot of progress in the Jupyter ecosystem, but unfortunately almost none in the areas you mentioned. - Source: Hacker News / 11 months ago
  • Ask HN: Fastest way to turn a Jupyter notebook into a website these days?
    Upload your ipynb to Deepnote and publish as an app. That simple. https://deepnote.com. - Source: Hacker News / about 1 year ago
  • Quick tip: Using a SingleStoreDB Recursive CTE with London Underground data
    Using Deepnote, we'll create a Python notebook and upload the two GeoJSON files into a data directory. - Source: dev.to / over 1 year ago
  • free-for.dev
    Deepnote - A new kind of data science notebook. Jupyter-compatible with real-time collaboration and running in the cloud. Free tier includes unlimited personal projects, up to 750 hours of standard hardware and teams with up to 3 editors. - Source: dev.to / over 1 year ago
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What are some alternatives?

When comparing Amazon Machine Learning and Deepnote, you can also consider the following products

Machine Learning Playground - Breathtaking visuals for learning ML techniques.

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

Lobe - Visual tool for building custom deep learning models

Apache Zeppelin - A web-based notebook that enables interactive data analytics.

Apple Machine Learning Journal - A blog written by Apple engineers

Saturn Cloud - ML in the cloud. Loved by Data Scientists, Control for IT. Advance your business's ML capabilities through the entire experiment tracking lifecycle. Available on multiple clouds: AWS, Azure, GCP, and OCI.

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