Software Alternatives, Accelerators & Startups

Scikit-learn VS Particle.io

Compare Scikit-learn VS Particle.io and see what are their differences

Scikit-learn logo Scikit-learn

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

Particle.io logo Particle.io

Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Particle.io Landing page
    Landing page //
    2023-09-23

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Particle.io videos

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!

Category Popularity

0-100% (relative to Scikit-learn and Particle.io)
Data Science And Machine Learning
IoT Platform
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Data Dashboard
60 60%
40% 40

User comments

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Reviews

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

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

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...

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Particle.io. It has been mentiond 28 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.

Scikit-learn mentions (28)

  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 3 months ago
  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 12 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: over 1 year ago
View more

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

What are some alternatives?

When comparing Scikit-learn and Particle.io, you can also consider the following products

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

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

OpenCV - OpenCV is the world's biggest computer vision library

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

NumPy - NumPy is the fundamental package for scientific computing with 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.