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Design Systems Repo VS Keras

Compare Design Systems Repo VS Keras and see what are their differences

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Design Systems Repo logo Design Systems Repo

A collection of design system examples and resources

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.
  • Design Systems Repo Landing page
    Landing page //
    2019-01-21
  • Keras Landing page
    Landing page //
    2023-10-16

Design Systems Repo features and specs

  • Comprehensive Collection
    Design Systems Repo offers an extensive collection of design systems and related resources from various organizations and companies, making it a valuable repository for designers and developers seeking inspiration or references.
  • Categorization
    Resources are categorized effectively, allowing users to navigate through different topics such as style guides, pattern libraries, and design tokens with ease.
  • Community Contributions
    The platform is open to contributions from the community, which means it is frequently updated with new and diverse design systems from around the world.
  • Educational Value
    Design Systems Repo serves as an educational tool by offering insights into how established companies structure their design systems, which can be beneficial for teams creating their own.
  • Free Access
    The platform is free to use, providing a cost-effective resource for teams and individuals looking to explore design systems without a financial barrier.

Possible disadvantages of Design Systems Repo

  • Quality Variation
    Since the content is user-contributed, the quality and thoroughness of design systems can vary significantly, leading to a mix of highly detailed and somewhat superficial resources.
  • Lack of Customization
    While comprehensive, the platform does not offer tools for customization or direct integration into a user’s workflow, limiting its utility beyond merely serving as a reference.
  • Outdated Resources
    There is no guarantee that all design system resources are up-to-date, which could mislead users if they rely on outdated practices or discontinued guidelines.
  • Search Functionality
    The search functionality might not be as robust as desired, potentially making it challenging to locate specific design systems or topics without thorough browsing.
  • Limited Interaction
    The platform focuses on curation rather than interaction, providing limited opportunities for users to discuss, critique, or ask questions about the design systems showcased.

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.

Analysis of Design Systems Repo

Overall verdict

  • Yes, Design Systems Repo is a highly regarded repository that is considered beneficial for individuals and teams involved in web and product design. It acts as a centralized hub for learning and inspiration, widely appreciated for its organized and curated content.

Why this product is good

  • Design Systems Repo offers a comprehensive collection of resources and tools that aid in the development and implementation of design systems. It provides links to various design system examples, articles, and tools, making it a valuable starting point for designers and developers who are looking to create or enhance their own design systems.

Recommended for

  • UI/UX designers
  • Front-end developers
  • Product managers
  • Design system enthusiasts
  • Teams building a unified design language

Analysis of Keras

Overall verdict

  • Keras is a solid choice for deep learning projects, offering simplicity and flexibility without sacrificing performance. It is well-suited for educational purposes, research, and even deploying models in production environments.

Why this product is good

  • Keras is widely regarded as a good deep learning library because it provides a user-friendly API that allows for easy and fast prototyping of neural networks. It is built on top of other libraries like TensorFlow, making it robust and efficient for both beginners and experienced developers. Its modularity, extensibility, and compatibility with other tools and libraries make it a popular choice for developing deep learning models.

Recommended for

  • Beginners who are new to deep learning
  • Researchers looking for an easy-to-use platform for prototyping models
  • Developers working on projects that require quick experimentation and development
  • Individuals and companies deploying models into production environments

Design Systems Repo videos

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Keras videos

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

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
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Category Popularity

0-100% (relative to Design Systems Repo and Keras)

Design Systems Repo

Keras

Design Tools
100 100%
Design Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Prototyping
100 100%
Prototyping
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 Design Systems Repo and Keras

Design Systems Repo Reviews

We have no reviews of Design Systems Repo yet.
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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, Keras should be more popular than Design Systems Repo. It has been mentiond 35 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.

Design Systems Repo mentions (6)

  • How do you keep yourself updated with the latest design trends?
    There is still some value in understanding aesthetic trends, it’s good to make sure your components and interactions are consistent with patterns people may be already familiar with. I like to nerd out on Design Systems Repo to view open source design system documentation. You can see how companies style their components, as well as how they work “under the hood” so to speak. I then like to compare it to their... Source: over 2 years ago
  • Making a Design Systems collection, any more out there you know?
    This is the site I use to browse design systems: Https://designsystemsrepo.com/. Source: over 2 years ago
  • Design Systems online?
    Yup this. Also https://designsystemsrepo.com is worth a flick through as they have some interesting alternate takes. Source: over 2 years ago
  • Ask HN: Good resources for programmers to learn about UX/design?
    Design Systems Repo - A frequently updated collection of Design System examples, articles, tools and talks https://designsystemsrepo.com/ Awesome Design Systems https://github.com/alexpate/awesome-design-systems. - Source: Hacker News / almost 3 years ago
  • Design system template or example
    So just to add to this source, you can also look around on https://designsystemsrepo.com They have a large collection of actual used design systems from companies around the world. Often times, their design systems are open to anyone. I’m not sure about the component library, but you can always check and see if they have a link. Source: over 3 years ago
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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 / about 1 month 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
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What are some alternatives?

When comparing Design Systems Repo and Keras, you can also consider the following products

Eva Design System - A free customizable design system

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.

Ant Design System for Figma - A large library of 2100+ handcrafted UI components

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

Invision - Prototyping and collaboration for design teams

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

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