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BuiltWith VS Scikit-learn

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

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The 6-signal founder validation companion. Score any startup idea on a 0-100 Launch Readiness Score across demand, pain, competition, money, funding, urgency. 1000+ ideas pre-scored. 200+ data sources. Daily refresh. featured
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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

BuiltWith logo BuiltWith

Find out the technology behind websites

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • BuiltWith Landing page
    Landing page //
    2023-04-16
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

BuiltWith features and specs

  • Comprehensive Technology Profiling
    BuiltWith provides detailed information about the technologies that websites are using, including analytics tools, content management systems, e-commerce platforms, and more. This can be incredibly useful for market research and competitive analysis.
  • Market Reports
    The platform offers in-depth market reports that can help businesses understand technology trends across different industries. This data can be crucial for strategic planning and technology adoption decisions.
  • Lead Generation
    BuiltWith can be used to generate leads by identifying websites that use specific technologies. This helps sales teams target potential clients who are already using a competitor's tool or a complementary technology.
  • Customizable Alerts
    Users can set up alerts to get notified whenever a website starts or stops using specific technologies. This feature helps businesses stay updated with market shifts and competitor movements in real-time.
  • Ease of Use
    The interface is relatively user-friendly, making it easy for users to search for websites and technologies without requiring any advanced technical skills.

Possible disadvantages of BuiltWith

  • Pricing
    BuiltWith can be quite expensive, particularly for small businesses and startups. The high cost may make it inaccessible for companies with limited budgets.
  • Data Accuracy
    While generally reliable, the data provided by BuiltWith may not always be 100% accurate or up-to-date. This can sometimes lead to incorrect assumptions or decisions based on outdated information.
  • Limited Free Features
    The free version of BuiltWith offers limited features and capabilities, which may not be sufficient for in-depth research or analysis. Users often need to upgrade to a premium plan to access the full range of functionalities.
  • Complex Data
    The detailed data and extensive lists of technologies can sometimes be overwhelming to sift through without specialized knowledge or a clear strategy, making it less useful for casual users.
  • Dependency on External Data
    BuiltWith relies on external data sources, which means that any limitations or issues with these sources can affect the quality and comprehensiveness of the information provided.

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 BuiltWith

Overall verdict

  • Yes, BuiltWith is considered a good resource for analyzing the technology behind websites due to its comprehensive data and ease of use. It is widely used by professionals to gain a competitive edge and to streamline technology-related decisions.

Why this product is good

  • BuiltWith is a valuable tool for web developers, marketers, and businesses as it provides insights into the technology stack of any website. It helps in understanding market trends, gaining competitive intelligence, and making informed decisions for technology adoption.

Recommended for

  • Web developers looking to understand how different sites are built and which technologies are used.
  • Digital marketers aiming to gather competitive insights and trend analysis.
  • Businesses wanting to assess potential technology partners and competitors.
  • Investors conducting due diligence on companies by understanding their technological 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.

BuiltWith videos

+ Add

How to Find Competitors Customers | BuiltWith Review | Kas Andz

More videos:

  • Review - Google Page Speed Tool, Comic-Con Website Review, and BuiltWith Anniversary by Matt@mywebbro.com

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 BuiltWith and Scikit-learn)

BuiltWith

Scikit-learn

Market Research
100 100%
Market Research
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Sales Automation
100 100%
Sales Automation
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using BuiltWith and Scikit-learn. For example, how are they different and which one is better?
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Reviews

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

BuiltWith Reviews

  1. Eleanor Bennett
    ยท Digital Marketing Specialist at Logit.io ยท
    Great for finding potential contacts

    A great tool to help you discover the technology being used by a variety of websites. I was impressed that upon signing up that I had full access to a free list of leads.

15 Best BuiltWith Alternatives 2022
Sometimes, BuiltWith may not fit your specific business needs. If so, weโ€™ve compiled our list of best BuiltWith alternatives you may want to consider for your profiling.
Source: rigorousthemes.com
8 Best SimilarWeb Alternatives (2019 UPDATE): Add These to Your Digital Tool Kit
BuiltWith is a truly comprehensive tool that will mine a ton of information from anyoneโ€™s site and serve it to you in a manner you will be able to crunch and use it. You might take your time since it is a lot of information to inform your decisions, which is a good thing.
Source: thedigitalmerchant.com
Best Similarweb Alternatives in 2019 to Spy on your Competitors
See business insights of your own business as well as get to know what keywords your competitors are using. Analyze your rivalsโ€™ budget and strategies. The top-notch companies tied with BuiltWith are Google, Adobe, Facebook, Amazon,eBay, and Paypal.
Source: affnext.com
The Best Email Marketing, Sales Prospecting, and Email Automation Software
Builtwith is a tool that helps in identifying sites that use specific web technologies. It identifies the technology spend, gathers the location information and vertical, among other option to create lead lists that are solid for websites by taking into account the internet footprint and technology usage.
Source: www.growthmarketingpro.com
73 Best SEO tools 2021 โ€“ The Most Epic List You Shouldnโ€™t Miss
BuiltWith offers a database of 7,000+ web technologies and more than 250 million websites to build lists for lead generation.
Source: blog.linkody.com

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, BuiltWith should be more popular than Scikit-learn. It has been mentiond 162 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.

BuiltWith mentions (162)

  • What Qualities Does It Take to Be the Best Software Developer
    Evan You, creator of Vue.js, is a prime example. Vivek Nair, Co-Founder of BotGauge, notes that You โ€œcreated something that addresses real developer needs with clean logic and thoughtful design.โ€ Vue.js powers over 1.5 million websites in 2025, a testament to its scalability and developer trust, as reported by BuiltWith. Youโ€™s ability to build a framework independently, without corporate backing, underscores his... - Source: dev.to / about 1 year ago
  • Web apps built with Ruby on Rails
    There exist websites like https://builtwith.com so answer to your question is yes. - Source: Hacker News / over 1 year ago
  • Ask HN: Tech Stack Behind the Claude App?
    BuiltWith says the web client is NextJS which is interesting as ChatGPT made a big switch away to Remix IIRC. https://builtwith.com/?https%3a%2f%2fclaude.ai%2fnew. - Source: Hacker News / almost 2 years ago
  • Disney's Robots Use Rockets to Stick the Landing
    Also, wow that is an obsene amount of libraries they use: https://builtwith.com/?https%3a%2f%2fspectrum.ieee.org%2fdisney-robot-2668135204. - Source: Hacker News / about 2 years ago
  • What website frameworks are used to build these websites?
    I would say run both sites through https://builtwith.com/ to get what all they used in the building process. Source: over 2 years ago
View more

Scikit-learn mentions (40)

  • Detecting Ingress Tool Transfer (T1105) with Python
    Certutil.exe or notepad.exe opening an external connection lands in rare because, fleet-wide, those processes almost never egress. Tune the <= 3 threshold to your environment size. For a more principled version, score each (process, destination) pair by frequency and treat the long tail as the hunt queue, which is the same idea behind scikit-learn's rarity-based anomaly methods without the model overhead. - Source: dev.to / about 2 months ago
  • Best AI Cybersecurity Training for Security Teams: How to Pick
    Pre-configured environment. A working VM or container with Jupyter, pandas, scikit-learn, and transformers already installed. Realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. If the first hour of training is fighting CUDA installs, the course is not ready. - Source: dev.to / about 2 months ago
  • Where to Get Hands-On AI Training for Cybersecurity Professionals
    Pre-configured environment. A good course ships a VM or container with Jupyter, pandas, scikit-learn, PyTorch or transformers, and realistic security datasets loaded. GTK Cyber students work in the Centaur VM, a free Apache 2.0 portable lab. No setup tax. - Source: dev.to / 2 months ago
  • How Anomaly Detection Actually Works in Security Operations
    Isolation-based models: Build random decision trees that split features. Points that are isolated quickly (short average path length across trees) are anomalies. IsolationForest in scikit-learn implements this. Handles high-dimensional feature spaces without assuming a distribution. - Source: dev.to / 3 months ago
  • Building a Personalized Meal Recommendation System
    In practice, youโ€™ll want to use libraries (like scikit-learn or TensorFlow.js for more advanced modeling), but the principle remains: find what similar users enjoy, and use that as a basis for recommendations. - Source: dev.to / 5 months ago
View more

What are some alternatives?

When comparing BuiltWith and Scikit-learn, you can also consider the following products

Wappalyzer - Wappalyzer is a technology profilers and leads data provider. Create lists of websites and contacts that use certain technologies.

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

WhatRuns - Extension that helps you identify technologies used on any website at the click of a button.

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

Elucify - A completely free software tool that uses crowdsourced data to find business email addresses

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

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