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GitHub Desktop VS Keras

Compare GitHub Desktop VS Keras and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

GitHub Desktop logo GitHub Desktop

GitHub Desktop is a seamless way to contribute to projects on GitHub and GitHub Enterprise.

Keras logo Keras

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
  • GitHub Desktop Landing page
    Landing page //
    2023-05-02
  • Keras Landing page
    Landing page //
    2023-10-16

GitHub Desktop features and specs

  • User-Friendly Interface
    GitHub Desktop offers a clean, intuitive GUI that simplifies the Git process, making it accessible for beginners and less technical users.
  • Seamless GitHub Integration
    The application is tightly integrated with GitHub, allowing users to easily clone repositories, create branches, and submit pull requests directly through the desktop interface.
  • Cross-Platform Support
    GitHub Desktop is available on both Windows and macOS, offering a consistent experience across these major operating systems.
  • Simplifies Workflow
    Features like drag-and-drop to add files, visual diff tools, and easy branching help streamline the workflow for users.
  • Collaborative Features
    The app provides useful collaborative tools such as reviewing changes, creating requests, and viewing history, enhancing team productivity.

Possible disadvantages of GitHub Desktop

  • Limited Advanced Features
    While GitHub Desktop is great for basic tasks, it lacks advanced features found in other Git clients like GitKraken or the command line.
  • Dependency on GitHub
    The app is deeply integrated with GitHub, which can be limiting for users who want to interact with repositories hosted on other platforms like GitLab or Bitbucket.
  • Performance Issues
    Some users report performance issues when dealing with large repositories or a significant number of files, which can hinder productivity.
  • Customization Limitations
    GitHub Desktop offers limited customization options compared to other Git clients or the command line, which may be a drawback for power users.
  • Offline Limitations
    Certain features of GitHub Desktop require an internet connection to interact with GitHub, limiting its usability in offline scenarios.

Keras features and specs

  • User-Friendly
    Keras provides a simple and intuitive interface, making it easy for beginners to start building and training models without needing extensive experience in deep learning.
  • Modularity
    Keras follows a modular design, allowing users to easily plug in different neural network components, such as layers, activation functions, and optimizers, to create complex models.
  • Pre-trained Models
    Keras includes a wide range of pre-trained models and offers easy integration with transfer learning techniques, reducing the time required to achieve good results on new tasks.
  • Integration with TensorFlow
    As part of TensorFlow’s ecosystem, Keras provides deep integration with TensorFlow functionalities, enabling users to leverage TensorFlow's powerful features and performance optimizations.
  • Extensive Documentation
    Keras has comprehensive and well-organized documentation, along with numerous tutorials and code examples, making it easier for developers to learn and use the framework.
  • Community Support
    Keras benefits from a large and active community, which provides support through forums, GitHub, and specialized user groups, facilitating the resolution of issues and sharing of best practices.

Possible disadvantages of Keras

  • Performance Limitations
    Due to its high-level abstraction, Keras may incur performance overheads, making it less suitable for scenarios requiring extremely fast execution and low-level optimizations.
  • Limited Low-Level Control
    The simplicity and abstraction of Keras can be a downside for advanced users who need fine-grained control over model components and custom operations, which may require them to resort to lower-level frameworks.
  • Scalability Issues
    In some complex applications and large-scale deployments, Keras might face scalability challenges, where more specialized or low-level frameworks could handle such tasks more efficiently.
  • Dependency on TensorFlow
    While the integration with TensorFlow is generally an advantage, it also means that the performance and features of Keras are closely tied to the development and updates of TensorFlow.
  • Lagging Behind Latest Research
    Keras, being a user-friendly high-level API, might not always incorporate the latest cutting-edge research advancements in deep learning as quickly as more research-oriented frameworks.

GitHub Desktop videos

+ Add

GitHub Desktop 2.0 -- Easy Mode Version Control

More videos:

  • Review - GitHub Desktop Quick Intro For Windows
  • Tutorial - Git and GitHub for Beginners: GitHub basics, and how to use GitHub Desktop

Keras videos

+ Add

3. Deep Learning Tutorial (Tensorflow2.0, Keras & Python) - Movie Review Classification

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
  • Review - EKOR KERAS!! Review and Bike Check DARTMOOR HORNET 2018 // MTB Indonesia

Category Popularity

0-100% (relative to GitHub Desktop and Keras)

GitHub Desktop

Keras

Git
100 100%
Git
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Code Collaboration
100 100%
Code Collaboration
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using GitHub Desktop and Keras. 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 GitHub Desktop and Keras

GitHub Desktop Reviews

Best Git GUI Clients of 2022: All Platforms Included
Creating branches and switching to existing ones isn’t a hassle, so is merging code with the master branch. Furthermore, you can track your changes with GitHub Desktop. Check out our detailed guide on how to use GitHub for more detailed information.
Source: www.hostinger.com
Boost Development Productivity With These 14 Git Clients for Windows and Mac
GitHub Desktop is the global standard for working with Git-related tasks in a graphical user interface (GUI). It is an open-source tool and hence completely free to use for all sorts of projects. It is available for both Windows and macOS desktops and laptops.
Source: geekflare.com
Best Git GUI Clients for Windows
GitHub Desktop is, perhaps, the most famous solution for working with Git in a visual interface. It is familiar to all developers keeping their repositories on GitHub (Git repository hosting service used for version-controlling IT projects). This free Git GUI is open-source, transparent, and functional. When you consider the Git graphical interface for Windows, GitHub...
Source: blog.devart.com

Keras Reviews

10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
15 data science tools to consider using in 2021
Keras is a programming interface that enables data scientists to more easily access and use the TensorFlow machine learning platform. It's an open source deep learning API and framework written in Python that runs on top of TensorFlow and is now integrated into that platform. Keras previously supported multiple back ends but was tied exclusively to TensorFlow starting with...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, GitHub Desktop should be more popular than Keras. It has been mentiond 135 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.

GitHub Desktop mentions (135)

  • How to Fix the Issue of Not Being Able to View Your GitHub Account on Other Devices
    Download the latest version from the GitHub Desktop website. - Source: dev.to / 5 months ago
  • 12 Steps to Organize and Maintain Your Python Codebase for Beginners
    I’m not going to dive into Git commands here — you can find plenty of tutorials online. If you’re not a fan of using the plain terminal CLI, you can also manage repositories with tools like GitHub Desktop or SourceTree, which provide a more visual, intuitive interface. - Source: dev.to / 7 months ago
  • File Governance and Versioning in Corticon BRMS
    Using terminal commands isn’t necessary for basic adoption of Git with Corticon Studio files, though. There are various tools that will allow us to bypass the command line when defining rules, including the built-in Eclipse plugin for Git version control. If you’ll be storing your assets on GitHub, though, an even easier solution is GitHub Desktop, a free desktop software that GitHub offers. It can be used in... - Source: dev.to / 8 months ago
  • An Introduction to Nix for Ruby Developers
    Nix currently is akin to git's "porcelain": powerful but esoteric. However, much like git evolved into exoteric, user-friendly tools such as git-flow, GitHub Desktop, and Tower to become user-friendly, many developers are building abstractions, wrappers, and utilities to simplify Nix usage. Let's briefly look at a few of these tools now. - Source: dev.to / 9 months ago
  • Make your first contribution on github easily
    1.Download the github desktop. 2.Open the first contribution repository. 3.Open the github app and clone the repository. - Source: dev.to / 11 months ago
View more

Keras mentions (35)

  • Top Programming Languages for AI Development in 2025
    The unchallenged leader in AI development is still Python. And Keras, and robust community support. - Source: dev.to / 24 days ago
  • Top 8 OpenSource Tools for AI Startups
    If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It lets you quickly prototype neural networks without worrying about low-level implementations. Keras is perfect for getting those first models up and running—an essential part of the startup hustle. - Source: dev.to / 7 months ago
  • Top 5 Production-Ready Open Source AI Libraries for Engineering Teams
    At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck. - Source: dev.to / 8 months ago
  • Using Google Magika to build an AI-powered file type detector
    The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 12 months ago
  • My Favorite DevTools to Build AI/ML Applications!
    As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 1 year ago
View more

What are some alternatives?

When comparing GitHub Desktop and Keras, you can also consider the following products

GitKraken - The intuitive, fast, and beautiful cross-platform Git client.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

SourceTree - Mac and Windows client for Mercurial and Git.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

SmartGit - SmartGit is a front-end for the distributed version control system Git and runs on Windows, Mac OS...

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

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