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Scikit-learn VS Java

Compare Scikit-learn VS Java 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.

Java logo Java

A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Java Landing page
    Landing page //
    2018-09-30

We recommend LibHunt Java for discovery and comparisons of trending Java 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.

Java features and specs

  • Platform Independence
    Java is known for its portability across multiple platforms via the Java Virtual Machine (JVM). This means you can write code once and run it anywhere.
  • Large Standard Library
    Java boasts a comprehensive standard library, which facilitates development by providing pre-built solutions for a wide array of programming tasks.
  • Robust and Secure
    Java emphasizes strong memory management and has built-in security features, making it a reliable choice for applications requiring high levels of security.
  • Community Support
    With a vast and active community, ample resources are available for learning and troubleshooting. Numerous libraries and frameworks are available due to its long-standing presence.
  • Performance
    Modern Java versions offer performance that is generally very good for many applications, particularly server-side applications where the Just-In-Time (JIT) compiler can significantly optimize runtime performance.

Possible disadvantages of Java

  • Verbosity
    Java's syntax can be verbose compared to newer languages, requiring more lines of code to accomplish the same tasks, which may reduce readability.
  • Memory Consumption
    Java applications can be memory-intensive due to their reliance on the JVM, which can be a downside for resource-constrained environments.
  • Performance Overhead
    Despite its generally good performance, Java's reliance on the JVM introduces some overhead compared to languages that compile to native machine code, such as C++.
  • No Low-Level Programming
    Java abstracts away from the hardware, making it less suitable for low-level programming tasks that require direct hardware manipulation, such as embedded systems programming.
  • Slow Startup Time
    Java applications can have slower startup times due to the overhead of JVM initialization, which can be a drawback for desktop applications or command-line tools that are frequently started and stopped.

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

Java videos

AP Computer Science in 10 Minutes (Java review)

More videos:

  • Review - Java AP CS Exam Review
  • Review - Top Five Basic Programming Concepts of Object-Oriented Java - Six Minute Refresher!

Category Popularity

0-100% (relative to Scikit-learn and Java)
Data Science And Machine Learning
Programming Language
0 0%
100% 100
Data Science Tools
100 100%
0% 0
OOP
0 0%
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 Java

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...

Java Reviews

The 10 Best Programming Languages to Learn Today
If you want to build your career in IoT or big data, Java is arguably the best programming language to learn. Java is cross-platform compatible and offers portability and versatility to almost any type of device, making it ideal for IoT applications. The Apache Hadoop big data processing system is also written in Java.
Source: ict.gov.ge
Alternatives to Nmap: from simple to advanced network scanning
This tool can provide favorite IP address ranges, NetBIOS information and web server detection. More features can be added by installing Java plugins.

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Java. 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 / 3 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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Java mentions (7)

  • Can someone help with port forwarding?
    You can use UPnP PortMapper. Source code/Download. All you need is Java and that's it. Hope this helps. Source: about 3 years ago
  • PolyGlot 3.5 Release
    I would definitely suggest installing Java for this one, and the error should have asked you to do so. I'll have to look into why that was not popping properly for you and address it in a bug fix. In the mean time, you can address the issue by going here to install Java: https://java.com/en/. Source: over 3 years ago
  • i need help pls
    Https://java.com/en/ Is this the java you're using to install optifine. When I first got optifine I thought java meant Minecraft and not java. Source: over 3 years ago
  • I keep getting this error when I try to install Worldpainter
    I had this problem before just go to https://java.com/en/ and download the java then you will have to install the actual java, then after its installed go to This PC then Windows then Program Files then Java then go to the file name file name that show I think when you downloaded it then go into bin and you will find a java.exe file then click it and World Painter will install and that's who I solved king problem... Source: over 3 years ago
  • What to do immediately with a brand new build?
    Java, Adobe Reader, Handbrake (great for converting and adjusting videos). Source: almost 4 years ago
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What are some alternatives?

When comparing Scikit-learn and Java, 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.

Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.

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

JavaScript - Lightweight, interpreted, object-oriented language with first-class functions

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

Rust - A safe, concurrent, practical language