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Stylebot VS Scikit-learn

Compare Stylebot VS Scikit-learn and see what are their differences

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Stylebot logo Stylebot

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

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Stylebot Landing page
    Landing page //
    2022-07-01
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Stylebot features and specs

  • User-Friendly Interface
    Stylebot offers an intuitive interface that makes it easy for users, even those with limited technical knowledge, to modify and apply custom styles to any website.
  • Customization
    It allows users to customize the appearance of any website by adjusting CSS styles, enabling a personalized browsing experience.
  • Real-Time Changes
    Changes made using Stylebot are applied instantly, allowing users to see the effects of their customizations in real-time.
  • Community-Driven
    Users can share their styles with the Stylebot community, providing access to a wide range of customizations and ideas.
  • Open Source
    Stylebot is open-source, which means it is constantly being improved by contributions from developers around the world.

Possible disadvantages of Stylebot

  • Learning Curve
    While its interface is user-friendly, those unfamiliar with CSS may still need time to learn how to create complex styles.
  • Compatibility Issues
    Some websites may not respond well to custom styles, potentially leading to broken layouts or functionality.
  • Limited Support
    Despite being popular, Stylebot may not have extensive professional support compared to commercial software.
  • Browser Specific
    As a browser extension, its functionality is limited to web browsers that support it, potentially excluding some users.
  • Security Concerns
    Using third-party extensions always comes with potential security risks, particularly if malicious styles are shared within the community.

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.

Stylebot videos

+ Add

Taking Control of Your Browsing Experience With Stylebot

More videos:

  • Review - reddit sidebar fix with stylebot

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 Stylebot and Scikit-learn)

Stylebot

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

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Reviews

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

Stylebot Reviews

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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, Scikit-learn should be more popular than Stylebot. It has been mentiond 31 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.

Stylebot mentions (14)

  • Here is a kMail iCloud theme
    In order to get this theme it on your browser, download the Stylebot extension for Chrome-based browsers or Firefox. Source: almost 2 years ago
  • I made CSS Pro, a re-imagined Devtools for web design
    If OP provides a list of actual differences and why the (imo) completely ridiculous price of css pro is justified, then I may consider it because I have a big web development project coming up and something like this (or just https://stylebot.dev) could come in really handy. Source: about 2 years ago
  • New "thumbs" design in the web version. I'm not a fan, so I've "fixed" them with Stylebot
    I've noticed a recent update in the web version introduced more "intrusive" thumbs reactions design. It's a matter of taste of course, but I don't like the new design so much. I wanted to share my solution, if someone is interested. I've used the extension Stylebot (for Chrome and Edge), that allows to "permanently" modify the css (stylesheet) of a website. Obviously it's only on your local browser 😃 I don't know... Source: about 2 years ago
  • Removing spoilers in Apple TV
    If you're watching in a browser, though, you can work around it by setting up rules for the website to add your own CSS to the page and hide the elements you don't want to see. I use an extension called Stylebot for this, but there are other options like Stylus or, if you're using Firefox, UserContent.css). I spent some time messing around with it and was able to remove everything I wanted with the CSS below. Source: over 2 years ago
  • I made a dark theme for Stremio
    Hi everyone! I made a dark theme for the Stremio web-app. I didn't really like the purple aesthetic of the official apps, which is why I made this and I thought some of you might like it. I used an extension called Stylebot to help make it since I have no experience with CSS (or any other programing language for that matter) and I think it turned out great for a first time. Source: over 2 years ago
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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 / about 2 years ago
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What are some alternatives?

When comparing Stylebot 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

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

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

Stylus - EXPRESSIVE, DYNAMIC, ROBUST CSS

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

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