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RegExr VS Keras

Compare RegExr VS Keras and see what are their differences

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RegExr logo RegExr

RegExr.com is an online tool to learn, build, and test Regular Expressions.

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.
  • RegExr Landing page
    Landing page //
    2023-07-28
  • Keras Landing page
    Landing page //
    2023-10-16

RegExr features and specs

  • User-Friendly Interface
    RegExr offers an intuitive and visually appealing interface that makes it easy for users to write, test, and understand regular expressions.
  • Real-time Feedback
    Changes to the regular expression and input text are reflected immediately, allowing users to see the effects of their adjustments in real-time.
  • Built-in Cheatsheet
    RegExr includes a handy cheatsheet that provides quick access to common regex patterns and syntax, making it easier for users to learn and reference rules.
  • Community Examples
    Users can explore and share community-generated regex patterns, which can serve as valuable examples or starting points for creating their own regex.
  • Detailed Explanation
    Each part of the regex pattern can be hovered over to display detailed tooltips explaining its function, aiding in the understanding of complex expressions.
  • Cross-Platform Accessibility
    As a web-based tool, RegExr can be accessed from any modern browser without the need for installation, making it convenient to use on multiple devices.

Possible disadvantages of RegExr

  • Limited Offline Use
    Since RegExr is a web-based application, it requires an internet connection, limiting its utility for users who need to work offline.
  • Learning Curve
    While the tool is user-friendly, users still need to have a foundational understanding of regular expressions to use RegExr effectively.
  • Performance Issues
    For extremely large inputs or very complex regular expressions, the tool may experience performance lags or slowdowns.
  • Limited Advanced Features
    RegExr may lack some advanced features found in more specialized or professional regex tools, such as integration with development environments or extensive scripting capabilities.
  • Privacy Concerns
    Users inputting sensitive data need to be cautious, as the web-based nature of the tool could raise privacy or data security concerns.

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 RegExr

Overall verdict

  • RegExr is widely regarded as an excellent tool for working with regular expressions due to its comprehensive feature set and ease of use.

Why this product is good

  • RegExr is considered a good tool for learning, creating, testing, and sharing regular expressions (regex). It offers a user-friendly interface, extensive documentation, real-time regex parsing, highlighting, and explanations, making it accessible for both beginners and experienced users. The platform provides a library of community-contributed patterns and a robust set of tools that helps users understand and construct regex patterns effectively.

Recommended for

  • Beginners learning regular expressions.
  • Developers needing to test and refine regex patterns.
  • Educators teaching regex concepts.
  • Anyone requiring an intuitive interface to work with regular expressions.

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

RegExr videos

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Keras videos

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 RegExr and Keras)
Programming Tools
100 100%
0% 0
Data Science And Machine Learning
Regular Expressions
100 100%
0% 0
Data Science Tools
0 0%
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 RegExr and Keras

RegExr Reviews

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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...

Social recommendations and mentions

Based on our record, RegExr seems to be a lot more popular than Keras. While we know about 367 links to RegExr, we've tracked only 35 mentions of Keras. 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.

RegExr mentions (367)

  • The importance of the environment in Regex pattern matching
    However - here it becomes weird - when testing the original regex rule (the first one, without the \u00A0 part) on the same string in an interactive visualiser (https://regexr.com/ for instance), there is a match:. - Source: dev.to / 8 months ago
  • Ask HN: How did you learn Regex?
    Learned regex in the 90's from the Perl documentation, or possibly one of the oreilly perl references. That was a time where printed language references were more convenient than searching the internet. Perl still includes a shell component for accessing it's documentation, that was invaluable in those ancient times. Perl's regex documentation is rather fantastic. `perldoc perlre` from your terminal. Or... - Source: Hacker News / 10 months ago
  • Ask HN: How did you learn Regex?
    I read a lot on https://www.regular-expressions.info and experimented on https://rubular.com since I was also learning Ruby at the time. https://regexr.com is another good tool that breaks down your regex and matches. One of the things I remember being difficult at the beginning was the subtle differences between implementations, like `^` meaning "beginning of line" in Ruby (and others) but meaning "beginning of... - Source: Hacker News / 10 months ago
  • Ask HN: How did you learn Regex?
    Mostly building things that needed complex RegEx, and debugging my regular expressions with https://regexr.com/. - Source: Hacker News / 10 months ago
  • Form Validation In TypeScipt Projects Using Zod and React Hook Form
    For username: You are using the min() function to make sure the characters are not below three and, then the max() function checks that the characters are not beyond twenty-five. You also make use of Regex to make sure the username must contain only letters, numbers, and underscore. - Source: dev.to / 11 months 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 RegExr and Keras, you can also consider the following products

regular expressions 101 - Extensive regex tester and debugger with highlighting for PHP, PCRE, Python and JavaScript.

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.

rubular - A ruby based regular expression editor

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

Expresso - The award-winning Expresso editor is equally suitable as a teaching tool for the beginning user of regular expressions or as a full-featured development environment for the experienced programmer with an extensive knowledge of regular expressions.

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