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Oh My Zsh VS Scikit-learn

Compare Oh My Zsh VS Scikit-learn and see what are their differences

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Oh My Zsh logo Oh My Zsh

A delightful community-driven framework for managing your zsh configuration.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Oh My Zsh Landing page
    Landing page //
    2023-09-19
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Oh My Zsh features and specs

  • Plugin Ecosystem
    Oh My Zsh offers a wide variety of plugins that extend the functionality of your shell, including git integration, syntax highlighting, and auto-suggestions.
  • Themes
    It provides a rich collection of themes that allow you to customize the look and feel of your terminal, making it visually appealing and easier to use.
  • Community Support
    With a large, active community, users can find a wealth of resources, tutorials, and support for troubleshooting and expanding their Zsh configuration.
  • Ease of Use
    Oh My Zsh simplifies the management of Zsh configurations through a straightforward installation process and easy-to-use commands for adding and removing plugins and themes.
  • Highly Configurable
    Even though it simplifies many aspects of Zsh, Oh My Zsh still allows for deep customization tailored to individual workflow needs.

Possible disadvantages of Oh My Zsh

  • Performance Overheads
    Using Oh My Zsh can slow down shell startup time, especially if many plugins or a complex theme are enabled.
  • Over-reliance on Plugins
    Users may become dependent on Oh My Zsh's extensive plugin system, which could discourage them from learning and understanding native Zsh scripting.
  • Potential for Conflicts
    Adding multiple plugins and custom scripts can lead to conflicts and bugs, making the shell environment unstable or unpredictable.
  • Large Install Size
    The framework with all its plugins and themes can take up a significant amount of disk space, which may be a consideration for users with limited storage.
  • Updates and Maintenance
    Regular updates are necessary to keep the system secure and up-to-date, which can be a hassle for users who prefer a 'set it and forget it' approach.

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.

Oh My Zsh videos

+ Add

You Really Don't Need Oh My Zsh And Here's Why (Rant)

More videos:

  • Review - Working with Linux - Terminal, Zsh & Oh My Zsh
  • Review - Uninstall Oh My ZSH Right Now And Do This Instead

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 Oh My Zsh and Scikit-learn)

Oh My Zsh

Scikit-learn

Developer Tools
100 100%
Developer Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Programming
100 100%
Programming
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Oh My Zsh and Scikit-learn. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Oh My Zsh and Scikit-learn

Oh My Zsh Reviews

  1. Stan
    · Founder at SaaSHub ·
    Indispensable

    This has become an indispensable tool for me. One of the first thing to install on a new computer.

    🏁 Competitors: GNU Bourne Again SHell, fish shell

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, Oh My Zsh should be more popular than Scikit-learn. It has been mentiond 74 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.

Oh My Zsh mentions (74)

  • Installing Terraform
    To start this re-learning journey, I feel like I should start with setting up a VPC on my AWS account. I already have an account so I will not be writing about that. However, since I want to do all of this via IaC, I need to setup Terraform. Luckily for me, this is a new laptop so I have nothing setup on it, besides iTerm2. Btw, I am using https://ohmyz.sh/ for my shell, so shout out to that team. This is what... - Source: dev.to / 16 days ago
  • Bash vs. Zsh: Key differences and when to use each
    Oh My Zsh is an open-source Zsh framework used to add extra functionalities for Zsh, turbocharging the entire Zsh user experience. Oh My Zsh’s extra advanced features cause users who frequently use the terminal to gravitate towards Zsh. - Source: dev.to / about 1 month ago
  • Switching from tmux to Zellij
    That's it! Happy CLI mastery with Zellij, Oh My zsh and Alacritty! - Source: dev.to / 2 months ago
  • The easiest way to set up and configure your AWS CLI
    If you are using Oh My ZSH as your shell of choice, you can add plugins=(... Aws ) to your .zshrc / profile and besides having autocomplete for the AWS CLI you will also immediately see in the terminal window what is the current AWS profile you are logged in. - Source: dev.to / 3 months ago
  • My Terminal Setup for 2025 🚀
    ZSH and Oh My ZSH offer superpowers to your terminal thanks to its customization and wide variety of plugins. - Source: dev.to / 4 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 / 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
View more

What are some alternatives?

When comparing Oh My Zsh and Scikit-learn, you can also consider the following products

Prezto - Prezto is the configuration framework for Zsh; it enriches the command line interface environment...

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

Starship (Shell Prompt) - Starship is the minimal, blazing fast, and extremely customizable prompt for any shell! Shows the information you need, while staying sleek and minimal. Quick installation available for Bash, Fish, ZSH, Ion, and Powershell.

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

Antigen - The plugin manager for zsh.

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

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