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Keras VS Ruby on Rails

Compare Keras VS Ruby on Rails and see what are their differences

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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.

Ruby on Rails logo Ruby on Rails

Ruby on Rails is an open source full-stack web application framework for the Ruby programming...
  • Keras Landing page
    Landing page //
    2023-10-16
  • Ruby on Rails Landing page
    Landing page //
    2023-10-23

We recommend LibHunt Ruby for discovery and comparisons of trending Ruby projects. Also, to find more open-source ruby alternatives, you can check out libhunt.com/r/rails

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.

Ruby on Rails features and specs

  • Rapid Development
    Ruby on Rails uses conventions over configurations which allows developers to build applications quickly. It comes with a wealth of built-in tools and libraries that streamline the development process.
  • Community Support
    Rails has a vibrant and active community. This means a lot of third-party libraries (gems) are available, and you can easily find help and resources.
  • Convention over Configuration
    Rails emphasizes convention over configuration, which reduces the number of decisions developers need to make. This can increase productivity and consistency across projects.
  • Built-in Testing
    Rails comes with a strong built-in testing framework, making it easier to test your application and ensure that it works as expected.
  • Scalability Options
    Although it has a reputation for not being the most scalable framework, Rails can be made scalable with good architecture and the right tools.
  • RESTful Design
    Rails promotes RESTful application design, which means that it aligns well with best practices in web development and makes it easier to build APIs.

Possible disadvantages of Ruby on Rails

  • Performance
    Ruby on Rails can be slower than some other frameworks, particularly for applications that require a lot of computation or have high traffic.
  • Learning Curve
    While Rails makes many things easier with its conventions, this can create a steep learning curve for newcomers who need to understand the 'Rails way' of doing things.
  • Scalability Concerns
    Due to its monolithic nature, scaling Rails can be challenging, requiring significant architectural changes and optimizations.
  • Lesser Flexibility
    The conventions that make Rails easy to use can also be limiting. When you need to do something outside the typical Rails flow, it may be harder to implement.
  • Runtime Speed
    Ruby, the language that Rails is built on, is generally slower in terms of execution speed compared to other languages like Java or C++.
  • Memory Consumption
    Rails applications can consume a lot of memory, which can be a concern for large-scale applications or those with limited resources.

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

Analysis of Ruby on Rails

Overall verdict

  • Ruby on Rails is generally considered a good choice for web development, especially for startups and small to medium-sized businesses looking to rapidly develop and iterate on their products.

Why this product is good

  • Ruby on Rails is a popular web application framework known for its simplicity and productivity. It offers a convention over configuration approach that speeds up the development process. Its strong community and rich ecosystem of gems make it easier for developers to implement complex functionalities quickly.

Recommended for

  • Startups looking to prototype quickly
  • Developers who prefer a simple and elegant syntax
  • Teams that prioritize rapid development
  • Applications that rely on CRUD operations

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

Ruby on Rails videos

+ Add

Ruby On Rails Biggest Waste Of Time In 2020 | Ruby on Rails Dead

More videos:

  • Tutorial - Ruby on Rails Tutorial | Build a Book Review App - Part 1

Category Popularity

0-100% (relative to Keras and Ruby on Rails)

Keras

Ruby on Rails

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Web Frameworks
0 0%
Web Frameworks
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 Keras and Ruby on Rails

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

Ruby on Rails Reviews

  1. Stan
    · Founder at SaaSHub ·
    The most productive web framework

    Yes, there are other more trending frameworks; however, nothing reaches the productivity of Rails. It's simply unbeatable if you have a small team.

    For example both SaaSHub and LibHunt were built on Rails.

    🏁 Competitors: Django, Laravel
Top 9 best Frameworks for web development
The best frameworks for web development include React, Angular, Vue.js, Django, Spring, Laravel, Ruby on Rails, Flask and Express.js. Each of these frameworks has its own advantages and distinctive features, so it is important to choose the framework that best suits the needs of your project.
Source: www.kiwop.com
Top 5 Laravel Alternatives
In terms of documentation, guidelines, and libraries, Ruby on Rails is the superior framework for smaller applications. Since it entered the online scene before Laravel, its community is larger and more well-liked among programmers. When compared to other Laravel alternatives, Ruby’s code is much simpler to understand and write.
Source: www.etatvasoft.com
Top 10 Phoenix Framework Alternatives
While modern frameworks try to minimize the tradeoffs to a limited extent, none of them has come closer to the implementation of the Phoenix Framework, which offers Ruby on Rails levels of productivity while being one of the fastest frameworks available in the market.
Source: blog.back4app.com
10 Ruby on Rails Alternatives For Web Development in 2022
Once a prolific web development technology, in 2021, both Ruby and Ruby on Rails are considered dying technologies. The data speaks for itself. In October 2021, Ruby lost 3 ranks in the Tiobe Index compared to October 2020 and became the 16th most searched programming language. The same decline in Ruby on Rails popularity is demonstrated by Google Trends. The language...
Source: www.ideamotive.co
Get Over Ruby on Rails — 3 Alternative Web Frameworks Worth Checking Out
Disclaimer: I started working on this article before the big controversy about Basecamp happened. I don’t want to make any point about this in the article. Regardless of what DHH and others are saying on different topics, Ruby on Rails is still a great piece of software and will continue to be. But there are some great alternatives as well that I would like to highlight.
Source: betterprogramming.pub

Social recommendations and mentions

Based on our record, Ruby on Rails should be more popular than Keras. It has been mentiond 143 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.

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 / 8 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 / about 1 year 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

Ruby on Rails mentions (143)

  • 🔥 Why Everyone Is Talking About HTMX: The Game-Changer for Web Development
    🌍 Who Should Use HTMX? ✅ Django / Flask / Rails developers ✅ Express / Node.js backend lovers ✅ Fullstack devs who want LESS frontend headache ✅ Teams jo SSR + SEO ko priority dete hain. - Source: dev.to / 14 days ago
  • Unlocking Opportunities: How to Thrive as a Ruby Engineer in Today's Tech Landscape
    Ruby on Rails open source projects. Contribute and learn at the same time. - Source: dev.to / about 1 month ago
  • Open Source: A Goldmine for Indie Hackers
    Speed of Development: Frameworks such as Django or Rails accelerate the development process. - Source: dev.to / about 1 month ago
  • Indie Hacking with Open Source Tools: Innovating on a Budget
    This ecosystem is fueled by repositories hosting powerful languages, functions, and versatile tools—from backend frameworks like Django and Ruby on Rails to containerization with Docker and distributed version control via Git. Moreover, indie hackers can also utilize open source design tools (e.g. GIMP, Inkscape) and analytics platforms such as Matomo. - Source: dev.to / about 1 month ago
  • Charybdis ORM: Building High-Performance Distributed Rust Backends with ScyllaDB
    Ruby on Rails (RoR) is one of the most renowned web frameworks. When combined with SQL databases, RoR transforms into a powerhouse for developing back-end (or even full-stack) applications. It resolves numerous issues out of the box, sometimes without developers even realizing it. For example, with the right callbacks, complex business logic for a single API action is automatically wrapped within a transaction,... - Source: dev.to / about 2 months ago
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What are some alternatives?

When comparing Keras and Ruby on Rails, you can also consider the following products

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.

Django - The Web framework for perfectionists with deadlines

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

Laravel - A PHP Framework For Web Artisans

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

ASP.NET - ASP.NET is a free web framework for building great Web sites and Web applications using HTML, CSS and JavaScript.

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