Software Alternatives, Accelerators & Startups

Scikit-learn VS Redox

Compare Scikit-learn VS Redox 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.

Redox logo Redox

Redox provides an EHR integration platform for digital health solutions.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Redox Landing page
    Landing page //
    2023-05-13

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

Redox videos

Redox Reactions: Crash Course Chemistry #10

More videos:

  • Tutorial - How To Balance Redox Reactions - General Chemistry Practice Test / Exam Review
  • Review - Electrochemistry Review - Cell Potential & Notation, Redox Half Reactions, Nernst Equation

Category Popularity

0-100% (relative to Scikit-learn and Redox)
Data Science And Machine Learning
Medical Practice Management
Data Science Tools
100 100%
0% 0
Practice Management
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 Scikit-learn and Redox

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...

Redox Reviews

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

Based on our record, Scikit-learn should be more popular than Redox. It has been mentiond 29 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 (29)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 20 days ago
  • 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 / 4 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 / about 1 year 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
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Redox mentions (14)

  • The First Stable Release of a Rust-Rewrite Sudo Implementation
    A Linux distro is going to need to see compiler to self-host regardless of the user land. If you can live without Linux, there's redox ( https://redox-os.org/ ). - Source: Hacker News / 8 months ago
  • Contributing to Open Source
    Redox is always open to contribution. Recently I've been helping with relibc, a mostly Rust libc. Source: about 1 year ago
  • How will HDR be implemented in COSMIC Rust?
    Well, considering the engineering team is managed by the same person that created Redox OS, then yes. I've personally been writing everything in Rust since Rust was still in alpha. Source: over 1 year ago
  • Is Iced replacing GTK apps for the new COSMIC desktop?
    The people bringing you Pop!_OS also created https://redox-os.org, and the whole team writes software in Rust. Source: almost 2 years ago
  • Ask HN: What Linux did NOT do right?
    You probably already know this, but "a capability-based microkernel written in Rust" describes RedoxOS. http://redox-os.org/. - Source: Hacker News / almost 2 years ago
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What are some alternatives?

When comparing Scikit-learn and Redox, 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.

Qvera Interface Engine (QIE) - Qvera's #1 ranked interface engine connects you to the healthcare networks & platforms that unlock your patient data enabling better efficiencies & outcomes

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

Change Healthcare Clinical Network Solutions - Other Health Care

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

Corepoint Integration Engine - Corepoint Integration Engine provides an enhanced approach to creating interfaces that gives users absolute confidence in connecting to external partners.