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Scikit-learn VS Scraping Fish

Compare Scikit-learn VS Scraping Fish and see what are their differences

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Scikit-learn logo Scikit-learn

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

Scraping Fish logo Scraping Fish

Scraping Fish is a super simple Web Scraping API. You send us a request - we return HTML. We use real browsers and rotating proxies underneath.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Scraping Fish Landing page
    Landing page //
    2022-10-29

Scraping Fish

Powered by Mobile Proxies

When using our API you leverage the power of the world's best proxies. Other web scraping services require you to pay much more to use proxies of such a quality. In Scraping Fish, this comes as the default - without additional configuration and included in price!

All our IPs are ethically sourced

Other web scraping services and proxy providers use unethical measures to get their IPs. Don't reinforce bad behavior - use ethical proxies. Every IP we use is ethically sourced.

Web Scraping Without The Hassle

Use the power of:

  • A Cluster of Real Browsers

  • JavaScript Rendering & Execution

  • Rotating Proxies

  • The Fastest Response Times

without the complexity of running it yourself. Always the same price - no matter which features you use.

Ingrained Simplicity

Scraping Fish was designed from the ground up to be the easiest scraping solution to integrate into your workflow and be used to get your web scraping business up and running quickly. You don't even need to setup an account - just buy request packs and get your API key delivered straight to your email.

Clear Pricing

  • $0.002 Per Request

  • All Features Included In Price

  • Failed Requests Not Charged

  • Requests Sold In Packs

Other web scraping services use API credits system which deliberately leads to confusion and benefits them at the cost of the user. Use Scraping Fish to always know the price of your web scraping job.

Scikit-learn

Website
scikit-learn.org
Pricing URL
-
$ Details
Platforms
-
Release Date
-
Edit details

Scraping Fish

Website
scrapingfish.com
Pricing URL
Official Scraping Fish Pricing
$ Details
paid $2.0 / One-off (1,000 API requests)
Platforms
Windows Linux Mac OSX Python JavaScript Java Node JS Ruby REST API Google Chrome Firefox Edge
Release Date
2022 March
Edit details

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.

Scraping Fish features and specs

  • Mobile Proxies
  • A Cluster of Real Browsers
  • JavaScript Rendering & Execution
  • Rotating Proxies
  • IPs are ethically sourced
  • Failed Requests Not Charged

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.

Scikit-learn videos

+ Add

Learning Scikit-Learn (AI Adventures)

More videos:

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

Scraping Fish videos

+ Add

100% Success Rate with This Proxy for Web Scrapers

Category Popularity

0-100% (relative to Scikit-learn and Scraping Fish)

Scikit-learn

Scraping Fish

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Extraction
0 0%
Data Extraction
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Web Scraping
0 0%
Web Scraping
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 Scraping Fish

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

Scraping Fish Reviews

We have no reviews of Scraping Fish yet.
Be the first one to post

Social recommendations and mentions

Scraping Fish might be a bit more popular than Scikit-learn. We know about 33 links to it since March 2021 and only 31 links to Scikit-learn. 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 (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 / 5 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 / 12 months 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 / about 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

Scraping Fish mentions (33)

  • Ask HN: What are you working on? (May 2025)
    Adding a support for direct CDP connection with our custom browsers cluster that powers our web scraping API (https://scrapingfish.com/) so that our customers can integrate it into their existing workflows. - Source: Hacker News / 5 days ago
  • Self-hosted, simple web browser service – send URL, get screenshots
    Happy to suggest another web scraping API alternative I rely on: https://scrapingfish.com. - Source: Hacker News / 4 months ago
  • Can confirm Indeed is selling user information
    > What is a good way to web scrap [sic] them Maybe using Scraping Fish [0]? Per [1], "They [scrapingfish.com] seem to handle all the more annoying parts of web scraping: bypassing anti scraping things such as rate limits and captchas." [0] https://scrapingfish.com/. - Source: Hacker News / 12 months ago
  • SaaS Subscription or Usage-Based Pricing?
    At https://scrapingfish.com/ we have both options, usage based https://scrapingfish.com/buy and subscriptions (monthly unlimited requests plan) https://scrapingfish.com/unlimited. Despite subscriptions being cheaper option per request, usage based is way more popular. Only less than 10% of our users have subscribed to unlimited monthly plan. I guess usage based plans give users more control over how much they... - Source: Hacker News / about 1 year ago
  • What is the most useful project you've ever worked on?
    I’m still working on a web scraping API (https://scrapingfish.com/). For some people it’s evil bot but for others it’s enabler for public data access. I thinks it’s useful. - Source: Hacker News / about 1 year ago
View more

What are some alternatives?

When comparing Scikit-learn and Scraping Fish, 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.

ScrapingBee - ScrapingBee is a Web Scraping API that handles proxies and Headless browser for you, so you can focus on extracting the data you want, and nothing else.

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

Zyte - We're Zyte (formerly Scrapinghub), the central point of entry for all your web data needs.

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

OnlineOrNot - Uptime monitoring for software teams (even teams of one).

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