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Particle.io VS AWS Personalize

Compare Particle.io VS AWS Personalize and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Particle.io logo Particle.io

Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.

AWS Personalize logo AWS Personalize

Real-time personalization and recommendation engine in AWS
  • Particle.io Landing page
    Landing page //
    2023-09-23
  • AWS Personalize Landing page
    Landing page //
    2023-04-01

Particle.io videos

+ Add

Particle All In One Face Cream For Men Review | thatsNathan

More videos:

  • Review - MEN'S SKIN CARE ROUTINE ! ( PARTICLE CREAM REVIEW )
  • Tutorial - THE BEST MEN'S SKIN CARE ROUTINE! ( PARTICLE FOR MEN FACE WASH REVIEW ) How To Have Great Skin!

AWS Personalize videos

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

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Category Popularity

0-100% (relative to Particle.io and AWS Personalize)

Particle.io

AWS Personalize

IoT Platform
100 100%
IoT Platform
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Dashboard
79 79%
Data Dashboard
21% 21
AI
0 0%
AI
100% 100

User comments

Share your experience with using Particle.io and AWS Personalize. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Particle.io and AWS Personalize

Particle.io Reviews

Best IoT Platforms in 2022 for Small Business
The IoT solutions offered by Particle are fully integrated and it is an easy to use IoT platform with built-in infrastructure. The particle’s operating system and the Device OS are the differentiators as it expedites the complex integration between firmware, hardware, and network connectivity on all Particle devices.
Source: www.fogwing.io
Open Source Internet of Things (IoT) Platforms
Self-describing as a “complete edge-to-cloud platform”, Particle.io also contains all the building blocks for developing an IoT product. This includes connectivity, device management, and even the hardware required to prototype IoT solutions and scale quickly thanks to the robust infrastructure. The platform supports IoT data collection and over-the-air development in a...
Source: jansutris10.medium.com

AWS Personalize Reviews

We have no reviews of AWS Personalize yet.
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Social recommendations and mentions

Based on our record, Particle.io should be more popular than AWS Personalize. It has been mentiond 9 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.

Particle.io mentions (9)

  • What hardware do I need for a robot to upload information to the cloud?
    Look into AWS Greengrass, Robomaker, etc. If you're looking for more customization. Or you could use an all-in-one product like from particle.io if you'd more of an out-of-the-box solution. Source: about 1 year ago
  • Web developer becoming embedded engineer?
    5) look at using a GPRS or LTE (look at particle.io) cell monitor a fridge or freezer. Source: over 2 years ago
  • KnowYourCrypto #51: BitTorrent Token (BTT)
    I really dig your KYC reports. Please do Particl particle.io next :). Source: over 2 years ago
  • Cloud solution for ESP8266
    That's not how I read the OP's proposal. It sounds more like they want to build something like the service that http://particle.io/ appears to provide. Source: almost 3 years ago
  • Ray Ozzie's latest venture is a cheap IoT board with flat rate connectivity
    Looks cool! How does this differ from http://particle.io ? - Source: Hacker News / almost 3 years ago
View more

AWS Personalize mentions (6)

  • Evolutionary Recommender Design with Amazon Personalize
    Over the past few months I've been spending a fair amount of time working on personalization, leveraging one of my new favorite AWS services - Amazon Personalize. Needless to say there is much more that goes into building and launching a personalization system than just turning on a few services and feeding in some data. In this article I'll focus on what it takes to launch a new personalization strategy, and... - Source: dev.to / 9 months ago
  • I built a ChatGPT powered shopping tool
    Check this out https://aws.amazon.com/personalize/. Source: about 1 year ago
  • Social Media Web app
    You can use Algolia Recommend system, comes at a cost or even AWS. Source: over 1 year ago
  • It's sad to watch Oura get cheaper and cheaper with their customers. First you just had to buy the ring. Next they gave you 6 months free. Now they give you one month free. They must be getting squeezed by their VCs/Board to turn up the margins.
    It's not sleep analysis, technically. They have general tools that analyze and process data in different ways. For example, AWS Personalize could be something useful for Oura. Source: over 1 year ago
  • Amazon SES and everything to set it up
    With Amazon Pinpoint and Amazon Personalize sending marketing emails with content customized to user's preference. - Source: dev.to / over 2 years ago
View more

What are some alternatives?

When comparing Particle.io and AWS Personalize, you can also consider the following products

AWS IoT - Easily and securely connect devices to the cloud.

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

ThingSpeak - Open source data platform for the Internet of Things. ThingSpeak Features

machine-learning in Python - Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.

Azure IoT Hub - Manage billions of IoT devices with Azure IoT Hub, a cloud platform that lets you easily connect, monitor, provision, and configure IoT devices.

Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.

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