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Scikit-learn VS Shareaholic

Compare Scikit-learn VS Shareaholic 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.

Shareaholic logo Shareaholic

Shareaholic is trusted by over 300000 brands, businesses, agencies, and individuals to grow website traffic and engagement 24 hours a day, 7 days a week.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Shareaholic Landing page
    Landing page //
    2023-09-13

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.

Shareaholic features and specs

  • Ease of Integration
    Shareaholic provides easy integration with various CMS platforms like WordPress, Shopify, and others. This allows for quick setup and minimal technical hassle.
  • Comprehensive Analytics
    The platform offers robust analytics that provide insights into social media sharing, traffic sources, and user behavior. This can help in optimizing content strategy.
  • Wide Range of Tools
    Shareaholic includes multiple tools such as social sharing buttons, related content recommendations, and content monetization options. This makes it a versatile tool for webmasters.
  • Customization Options
    The platform offers various customization options for sharing buttons and other tools, which allow for a better fit with the website's design and functionality.
  • Performance Optimization
    Shareaholic includes features for performance optimization, ensuring that the added functionalities do not significantly impact site loading times.

Possible disadvantages of Shareaholic

  • Cost
    While Shareaholic offers a free plan, many advanced features require a paid subscription, which may not be affordable for smaller websites or individual bloggers.
  • Data Privacy
    Some users have expressed concerns about data privacy and how Shareaholic handles user data, particularly with its tracking features.
  • Customer Support
    There have been reports of less-than-satisfactory customer support, especially for users on the free plan who may experience delays in getting issues resolved.
  • Complexity for Beginners
    Although the tool is feature-rich, it may be somewhat overwhelming for beginners due to the numerous options and settings available.
  • Compatibility Issues
    In some cases, users have reported compatibility issues with certain themes or other plugins, which could lead to functionality problems on the website.

Scikit-learn videos

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Learning Scikit-Learn (AI Adventures)

More videos:

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

Shareaholic videos

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Shareaholic WordPress plugin- social share buttons

Category Popularity

0-100% (relative to Scikit-learn and Shareaholic)

Scikit-learn

Shareaholic

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Social Media Tools
0 0%
Social Media Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Advertising
0 0%
Advertising
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 Shareaholic

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

Shareaholic Reviews

We have no reviews of Shareaholic yet.
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Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. 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.

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
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Shareaholic mentions (0)

We have not tracked any mentions of Shareaholic yet. Tracking of Shareaholic recommendations started around Mar 2021.

What are some alternatives?

When comparing Scikit-learn and Shareaholic, 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.

AddThis - AddThis free website tools include share buttons, targeting tools and content recommendations help you get more likes, shares and followers and keep them coming back.

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

AdSense - Earn money with website monetization from Google AdSense. We'll optimize your ad sizes to give them more chance to be seen and clicked.

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

ShareThis - Grow your audience with easy-to-use sharing tools.

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