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Scikit-learn VS Learn X in Y minutes

Compare Scikit-learn VS Learn X in Y minutes 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.

Learn X in Y minutes logo Learn X in Y minutes

LearnXinYminutes isn’t a good way to learn your first programming language, but it’s a great way to...
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • Learn X in Y minutes Landing page
    Landing page //
    2019-09-04

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.

Learn X in Y minutes features and specs

  • Concise Learning
    Learn X in Y minutes offers brief and straight-to-the-point introductions to programming languages and tools, making it ideal for quick learning.
  • Wide Range of Topics
    The platform covers a diverse array of programming languages and technologies, providing a useful resource for exploring new areas.
  • Code Examples
    Includes practical code snippets and examples, aiding in the comprehension and application of the presented material.
  • Community Contributions
    Open to community input and contributions, allowing for up-to-date and continuously expanding content.

Possible disadvantages of Learn X in Y minutes

  • Lack of Depth
    Due to the concise nature, the material often lacks depth and may not cover advanced topics thoroughly.
  • Limited Learning Style
    May not suit learners who prefer detailed explanations or a slower, more gradual educational approach.
  • Inconsistency in Quality
    Community contributions can lead to varying quality and consistency across different topics.
  • Minimal Visual Aids
    Primarily text-based with limited visual aids, which can be challenging for visual learners or complex concepts.

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

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Category Popularity

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Data Science And Machine Learning
Online Learning
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Data Science Tools
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Online Education
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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 Learn X in Y minutes

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...

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Social recommendations and mentions

Based on our record, Learn X in Y minutes should be more popular than Scikit-learn. It has been mentiond 149 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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Learn X in Y minutes mentions (149)

  • How would you start to learn coding today?
    I can't fathom it, but if I had to start over today, I'd: - Pick something I want to build - Pick the tools -- whatever's at the top of the latest SlackOverflow survey, though I'm not sure SO matters anymore - Peruse the https://learnxinyminutes.com link for the chosen tools - Use an LLM with good prompting to assist me in making what I decided. I'd use chat and hand type the code from the LLM and try to... - Source: Hacker News / 4 months ago
  • 100+ FREE Resources Every Web Developer Must Try
    . HTML Cheat Sheet: Quick reference guide for HTML elements and attributes. . CSS Cheat Sheet: Comprehensive guide to CSS properties and selectors. . JavaScript Cheat Sheet: Handy reference for JavaScript syntax and concepts. . Git Cheat Sheet: Essential commands and workflows for Git. . Markdown Cheat Sheet: Markdown syntax guide for creating rich text formatting. . React Cheat Sheet: Quick overview of React... - Source: dev.to / 10 months ago
  • Lua: The Modular Language You Already Know
    This is a small code example to get the basic idea. If you want a bit of a bigger file to play around yourself Or ever want to learn about a new language you can use LearnXinYMinutes which is a great starting point to learn any language you desire. - Source: dev.to / 11 months ago
  • Scripts should be written using the project main language
    > Sure, maybe for some esoteric edge cases, but 5 mins on https://learnxinyminutes.com/ should get you 80% of the way there, and an afternoon looking at big projects or guidelines/examples should you another 18% of the way. Not for C++, and even for other languages, it's not the language that's hard, it's the idioms. Python written by experts can be well-nigh incomprehensible (you can save typing out... - Source: Hacker News / about 1 year ago
  • Scripts should be written using the project main language
    > Learning a new language shouldn't be difficult. Programmers are expected to familiarize themselves with new tech. I wish any large company agreed with this. I've worked for a company that on boarded every single new engineer to a very niche language (F#) in a few days. Also, everybody I worked with there was amazing. Probably because of that kind of mindset. Meanwhile google tiptoes around teams adopting kotlin... - Source: Hacker News / about 1 year ago
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What are some alternatives?

When comparing Scikit-learn and Learn X in Y minutes, 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.

Exercism - Download and solve practice problems in over 30 different languages.

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

DevDocs - Open source API documentation browser with instant fuzzy search, offline mode, keyboard shortcuts, and more

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

OverAPI - Largest cheat sheet for programming languages and libraries