Software Alternatives, Accelerators & Startups
Register | Login

Stylus - User Styles Manager VS Scikit-learn

Compare Stylus - User Styles Manager VS Scikit-learn and see what are their differences

ScreenshotMAX
The all-in-one Screenshot API for developers: capture websites, generate PDFs, record videos, and automate it all with powerful, scalable infrastructure. No browser setup, no hassle. Just clean results, fast. featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Stylus - User Styles Manager logo Stylus - User Styles Manager

Stylus is a userstyles editor and manager based on the source code of Stylish version 1.5.2.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Stylus - User Styles Manager Landing page
    Landing page //
    2023-01-05
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Stylus - User Styles Manager features and specs

  • Customization
    Stylus allows users to fully customize the appearance of websites by applying user-created CSS styles, enabling a personalized browsing experience.
  • Ease of Use
    The interface is user-friendly and intuitive, making it easy for both beginners and advanced users to manage and apply user styles.
  • Open Source
    Stylus is open-source software, which means it is developed collaboratively and transparently, with community-driven improvements and security.
  • CSS Preprocessor Support
    Stylus supports using preprocessors, allowing users to write more organized and reusable CSS with variables, nested rules, and more.
  • Community and Library
    Stylus has a strong community and access to a large library of pre-made user styles that can be easily discovered and installed.

Possible disadvantages of Stylus - User Styles Manager

  • Compatibility Issues
    Some user styles may not work properly with certain websites or may require regular updates due to changes in website code.
  • Performance Concerns
    Applying complex styles can sometimes lead to increased browser resource consumption and slower page loading times.
  • Security Risks
    Downloading and applying user-generated styles can potentially introduce security issues if malicious code is injected.
  • Learning Curve
    Users who are unfamiliar with CSS may face a learning curve when trying to create custom styles from scratch.
  • Limited Browser Support
    Stylus might not be supported across all browsers, limiting its use to those that provide the necessary extension infrastructure.

Scikit-learn features and specs

  • Ease of Use
    Scikit-learn provides a high-level interface for common machine learning algorithms, making it easy for beginners and professionals to implement complex models with minimal coding.
  • Extensive Documentation and Community Support
    The library has comprehensive documentation and a large, active community. This makes it easy to find tutorials, examples, and solutions to common problems.
  • Integration with Other Libraries
    Scikit-learn integrates well with other scientific computing libraries such as NumPy, SciPy, and pandas, allowing for seamless data manipulation and analysis.
  • Variety of Algorithms
    It offers a wide array of machine learning algorithms for tasks such as classification, regression, clustering, and dimensionality reduction.
  • Performance
    Designed with performance in mind, many of the algorithms are optimized and some even support multicore processing.

Possible disadvantages of Scikit-learn

  • Limited Deep Learning Support
    Scikit-learn is primarily focused on traditional machine learning algorithms and does not offer support for deep learning models, unlike libraries like TensorFlow or PyTorch.
  • Not Ideal for Large-Scale Data
    While Scikit-learn performs well for moderate-sized datasets, it may not be the best choice for extremely large datasets or big data applications.
  • Lack of Online Learning Algorithms
    The library has limited support for online learning algorithms, which are useful for scenarios where data arrives in a stream and model needs to be updated incrementally.
  • Less Flexibility in Customization
    It can be less flexible compared to lower-level libraries when highly customized or specific implementations are needed.
  • Dependency Overhead
    Scikit-learn relies on several other Python libraries like NumPy and SciPy, which might require users to manage multiple dependencies.

Analysis of Scikit-learn

Overall verdict

  • Yes, Scikit-learn is generally regarded as a good library for machine learning, especially for beginners and intermediate users who need reliable tools with efficient implementation of numerous algorithms.

Why this product is good

  • Scikit-learn is considered a good machine learning library because it provides a wide range of state-of-the-art algorithms for supervised and unsupervised learning. It is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. The library is well-documented, easy to use, and has a consistent API that simplifies the integration of different algorithms. Furthermore, there's a strong community and continuous development, which means it is well-maintained and updated regularly with new features and improvements.

Recommended for

  • Beginners learning machine learning concepts and application.
  • Data scientists and engineers looking for a robust and efficient toolkit to build and deploy machine learning models.
  • Researchers who need an easy-to-use library that facilitates the experimentation of various algorithms.
  • Developers who require a seamless, Python-based machine learning library that integrates well with other data analysis tools and environments.

Stylus - User Styles Manager videos

No Stylus - User Styles Manager videos yet. You could help us improve this page by suggesting one.

Add video

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

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

Category Popularity

0-100% (relative to Stylus - User Styles Manager and Scikit-learn)

Stylus - User Styles Manager

Scikit-learn

Browser Extension
100 100%
Browser Extension
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Stylus - User Styles Manager and Scikit-learn. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Stylus - User Styles Manager and Scikit-learn

Stylus - User Styles Manager Reviews

We have no reviews of Stylus - User Styles Manager yet.
Be the first one to post

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...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, Stylus - User Styles Manager should be more popular than Scikit-learn. It has been mentiond 48 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.

Stylus - User Styles Manager mentions (48)

  • How to Customize Slack Fonts Using Stylus for Improved Readability
    Stylus is a browser extension that allows you to apply custom CSS to any website. Https://add0n.com/stylus.html. - Source: dev.to / 12 months ago
  • Make GoodReads 15% Less Annoying with One Weird Trick!
    Both of these are hosted on userstyles.world. To use them, you'll need to have a browser extension like Stylus . Then just click the blue Install button for each tool you want! Source: almost 2 years ago
  • Promote Your Work! July 2023 Self-Promotion thread
    These are both hosted on userstyles.world. I recommend using them with the Stylus browser extension, which works on Chrome, Firefox (including Firefox Nightly for Android) and Opera. (Pretty sure it will also work with Cascadea if you're on Safari but I haven't tested it yet.). Source: almost 2 years ago
  • Any way to make lemmy look more like old reddit?
    I wonder if Stylus would be good for this... Source: about 2 years ago
  • I tweaked satisfactory-calculator.com to be better for wide monitors!
    If you don't have a userstyles extension installed, you can get one here for Firefox or Chrome, but for Safari you'll have to do some tweaking. Source: about 2 years ago
View more

Scikit-learn mentions (31)

  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
  • 🚀 Launching a High-Performance DistilBERT-Based Sentiment Analysis Model for Steam Reviews 🎮🤖
    Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 6 months ago
  • 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 / about 1 year 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 / over 1 year 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 / almost 2 years ago
View more

What are some alternatives?

When comparing Stylus - User Styles Manager and Scikit-learn, you can also consider the following products

Dark Reader - Reduce eye strain in your browser with this extension that provides a dark theme for browsing.

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

Stylebot - Change the appearance of websites instantly. Preview and install styles created by other users on stylebot.me

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

Amino Editor - Amino is a Chrome browser extension for customizing web page presentation with user CSS.

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

Loading...