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Apify VS Scikit-learn

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

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LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Contents:
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  3. » Reviews
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Apify logo Apify

Apify is a web scraping and automation platform that can turn any website into an API.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Apify Landing page
    Landing page //
    2023-09-30

Apify is a JavaScript & Node.js based data extraction tool for websites that crawls lists of URLs and automates workflows on the web. With Apify you can manage and automatically scale a pool of headless Chrome / Puppeteer instances, maintain queues of URLs to crawl, store crawling results locally or in the cloud, rotate proxies and much more.

  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Apify features and specs

  • Ease of Use
    Apify provides a user-friendly interface that makes it easy for users of all technical levels to create and manage web scraping tasks.
  • Scalability
    Apify is built to handle tasks of various sizes, from small-scale projects to enterprise-level operations, making it a scalable solution.
  • Integration and API Support
    It offers extensive API support, allowing for seamless integration with other tools and systems to enhance automated workflows.
  • Customizability
    Users can customize their scraping bots (actors) with different settings and scripts to fit specific needs and requirements.
  • Cloud-based
    Being a cloud-based platform, Apify allows users to run their scraping tasks without needing local resources, which is convenient and efficient.
  • Comprehensive Documentation
    Apify provides thorough documentation and tutorials, which help users get started quickly and solve issues efficiently.
  • Community and Support
    Apify has an active community and solid customer support to assist users with their needs and enhance their overall experience.

Possible disadvantages of Apify

  • Learning Curve
    While the interface is user-friendly, there may still be a learning curve for those new to web scraping and automation.
  • Cost
    Apify can be expensive compared to other web scraping tools, particularly for extensive use cases that require high volumes of data.
  • Dependency on External Factors
    Web scraping often depends on the stability of the target websites. Changes in website structures can break scripts, requiring ongoing maintenance.
  • Performance Limitations
    The performance of cloud-based scraping tasks can be affected by network latency and other external factors beyond user control.
  • Potential Legal Issues
    Web scraping can raise legal concerns, particularly when scraping data from websites that restrict such activities in their terms of service.
  • Resource Intensity
    Complex scraping tasks can be resource-intensive, potentially requiring higher-tier subscriptions and more computing resources, driving up costs.

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.

Apify videos

+ Add

Apify product news - 2019/01/30

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 Apify and Scikit-learn)

Apify

Scikit-learn

Web Scraping
100 100%
Web Scraping
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Data Extraction
100 100%
Data Extraction
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 Apify and Scikit-learn

Apify Reviews

Top 15 Best TinyTask Alternatives in 2022
This is another tinytask alternative. For you to link various web services and APIs, Apify has provided many web integration options. You can add data processing and customised computation processes in addition to letting the data flow between them. With the data that is freely accessible on the web, you may provide crucial insights, and easy lead creation allows you to...
Source: www.dashtech.org

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

Scikit-learn might be a bit more popular than Apify. We know about 31 links to it since March 2021 and only 26 links to Apify. 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.

Apify mentions (26)

  • How to scrape TikTok using Python
    For deployment, we'll use the Apify platform. It's a simple and effective environment for cloud deployment, allowing efficient interaction with your crawler. Call it via API, schedule tasks, integrate with various services, and much more. - Source: dev.to / 24 days ago
  • How to scrape Bluesky with Python
    We already have a fully functional implementation for local execution. Let us explore how to adapt it for running on the Apify Platform and transform in Apify Actor. - Source: dev.to / 2 months ago
  • Web scraping with GPT-4o: powerful but expensive
    We've had the best success by first converting the HTML to a simpler format (i.e. markdown) before passing it to the LLM. There are a few ways to do this that we've tried, namely Extractus[0] and dom-to-semantic-markdown[1]. Internally we use Apify[2] and Firecrawl[3] for Magic Loops[4] that run in the cloud, both of which have options for simplifying pages built-in, but for our Chrome Extension we use... - Source: Hacker News / 9 months ago
  • Current problems and mistakes of web scraping in Python and tricks to solve them!
    Developed by Apify, it is a Python adaptation of their famous JS framework crawlee, first released on Jul 9, 2019. - Source: dev.to / 9 months ago
  • Show HN: Crawlee for Python – a web scraping and browser automation library
    Hey all, This is Jan, the founder of [Apify](https://apify.com/)—a full-stack web scraping platform. After the success of [Crawlee for JavaScript](https://github.com/apify/crawlee/) today! The main features are: - A unified programming interface for both HTTP (HTTPX with BeautifulSoup) & headless browser crawling (Playwright). - Source: Hacker News / 11 months 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 / 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 / 11 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

What are some alternatives?

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

import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.

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

Scrapy - Scrapy | A Fast and Powerful Scraping and Web Crawling Framework

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

ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.

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

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