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DevExtreme VS Scikit-learn

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

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

DevExtreme logo DevExtreme

HTML5 Widgets & SPA Framework for Desktop and Mobile

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • DevExtreme Landing page
    Landing page //
    2021-07-29
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

DevExtreme features and specs

  • Comprehensive Widget Library
    DevExtreme offers a wide range of UI widgets for data visualization, data editing, and navigation, providing developers with the tools they need to build feature-rich applications.
  • Cross-Platform Compatibility
    DevExtreme supports multiple frameworks including Angular, React, Vue, and jQuery, enabling developers to create applications across various platforms and devices.
  • Rich Data Visualization
    The library includes advanced data visualization components like charts, gauges, and pivot grids, allowing developers to present data in interactive and visually appealing ways.
  • Responsive Design
    Widgets in DevExtreme are designed to be responsive and adaptable to different screen sizes and orientations, ensuring a consistent user experience across devices.
  • Robust Documentation and Support
    DevExtreme provides comprehensive documentation, examples, and a dedicated support team, which can help developers efficiently integrate and troubleshoot components.

Possible disadvantages of DevExtreme

  • Licensing Costs
    DevExtreme is a commercial product that requires a paid license for use, which could be a limitation for startups or individual developers with limited budgets.
  • Learning Curve
    With such a wide array of features and customization options, developers may face a steep learning curve before becoming proficient in using the library effectively.
  • Performance Overhead
    Incorporating many complex widgets and features can lead to performance issues, especially in applications that require real-time data processing or operate in resource-constrained environments.
  • Dependency on Vendor
    Relying on a third-party UI library can create dependency on the vendor for updates and new features, which may not always align perfectly with a projectโ€™s timelines or specific needs.
  • Initial Setup Complexity
    The initial setup and configuration of DevExtreme in a project can be complex, especially for teams that are new to the library or are integrating it into existing projects.

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.

DevExtreme videos

+ Add

DevExtreme React Grid: Getting Started - Part 1

More videos:

  • Review - New in v18.1 - DevExtreme HTML/JS Controls

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 DevExtreme and Scikit-learn)

DevExtreme

Scikit-learn

Design Tools
100 100%
Design Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Development Tools
100 100%
Development 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 DevExtreme and Scikit-learn

DevExtreme 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 DevExtreme. It has been mentiond 40 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.

DevExtreme mentions (5)

  • Nuxt Tutorial 7 - UI Integrations
    The DevExtreme UI library was first introduced to me by an โ€œAngular guyโ€ colleague. Itโ€™s framework agnostic though, so you can use it in Vue as well. The main downside is obvious right away: itโ€™s paid โ€” and not cheap. On the other hand, we used it on a larger real-world project at work, and I have to say building complex nested forms (assembled entirely from scratch) was incredibly smooth with DevExtreme. Their... - Source: dev.to / 6 months ago
  • Didact | A New .NET Job Orchestration Platform
    I was going to exclusively use DevExtreme for the entire UI, but I really, really like Tailwind CSS, so I think I'm going to use DevExtreme for the tables, filtering, and charting, and for the rest I think I might use something like Flowbite. Source: almost 3 years ago
  • .NET Modern Task Scheduler
    DevExtreme components for powerful datagrids and filtering. Source: over 3 years ago
  • Need a datagrid that allows to execute the mentioned feature requirement.
    I'm using DevExtreme in one of my project, which is a suite of components that's relatively cheap for what's included but powerful. The only downside is it's a general purpose library of components, so it doesn't always feel "Angular native". Other than that the included data grid can render custom content using a master-detail view. There's also a "tree list" component included if you need to visualize actual... Source: over 3 years ago
  • MAUI, Blazor, Avalonia, Uno... isn't there a simple UI abstraction in .NET?
    Take a commercial framework which offers a lot of components and good support (like DevExpress DevExtreme for example) and build an SPA application with some sort of a REST backend. Source: over 3 years ago

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 1 month 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 1 month 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 / about 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 / 2 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 / 4 months ago
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What are some alternatives?

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

Material UI - A CSS Framework and a Set of React Components that Implement Google's Material Design

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

Ionicons - Ionicons offers fonts for Ionic Framework.

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

Chakra UI - Simple, modular and accessible UI components for your React applications.

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

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