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Keras VS Apache Struts

Compare Keras VS Apache Struts 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.

Apache Struts logo Apache Struts

Apache Struts is an open-source web application framework for developing Java EE web applications.
  • Keras Landing page
    Landing page //
    2023-10-16
  • Apache Struts Landing page
    Landing page //
    2022-04-27

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.

Apache Struts features and specs

  • Robust Framework
    Apache Struts is a mature and well-established framework for Java web applications, providing stable and reliable tools for enterprise-level applications.
  • MVC Architecture
    Struts adheres to the Model-View-Controller (MVC) design pattern, which separates business logic, presentation, and navigation, making code maintenance and development easier.
  • Extensive Documentation
    Struts has comprehensive documentation and a wealth of online resources, including tutorials, community forums, and user guides, which can support developers throughout their projects.
  • Rich Tag Library
    It comes with a rich set of custom tags that enhance the JSP (JavaServer Pages) to create dynamic web content easily.
  • Plugin Support
    Apache Struts supports various plugins that can extend its functionality, allowing developers to integrate additional features without much effort.

Possible disadvantages of Apache Struts

  • Steep Learning Curve
    New developers might find Struts challenging to learn due to its complexity and the need for a good understanding of the MVC architecture and Java web application development.
  • Configuration Overhead
    The framework requires extensive XML configuration, which can be cumbersome and time-consuming compared to convention-over-configuration frameworks.
  • Performance
    Struts can be slower than some newer, lighter frameworks due to its broader feature set and the overhead associated with its extensive configuration.
  • Security Vulnerabilities
    Struts has had notable security vulnerabilities in the past. Although patches and updates are available, it necessitates proactive monitoring and maintenance.
  • Outdated Compared to Modern Frameworks
    With the advent of modern frameworks like Spring MVC and JavaServer Faces, some developers consider Struts to be less up-to-date with the latest web development standards and practices.

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 Apache Struts

Overall verdict

  • Apache Struts is a robust framework, suitable for building Java-based web applications, but it's crucial to stay vigilant regarding security updates.

Why this product is good

  • Apache Struts is known for its MVC framework, which is useful for creating well-structured and maintainable Java applications. It provides a range of comprehensive features like a flexible tag library, integration with other Java frameworks, and a strong support community. However, it has faced some high-profile security vulnerabilities in the past, underscoring the importance of keeping the framework timely updated.

Recommended for

  • Organizations developing enterprise-level Java applications
  • Developers familiar with Java and looking for a robust MVC framework
  • Teams interested in integrating their web applications with other Java technologies

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

Apache Struts videos

Finding and Fixing Apache Struts CVE-2017-5638 with Black Duck Hub

More videos:

  • Review - Apache Struts 2 - remote command execution
  • Review - Dark ambient drone music | Vulnerable Apache Struts installation under attack (Java, Jakarta)

Category Popularity

0-100% (relative to Keras and Apache Struts)
Data Science And Machine Learning
Developer Tools
0 0%
100% 100
OCR
100 100%
0% 0
Web Frameworks
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 Keras and Apache Struts

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...

Apache Struts Reviews

17 Popular Java Frameworks for 2023: Pros, cons, and more
You can integrate Struts with other Java frameworks to perform tasks that aren’t built into the platform. For instance, you can use the Spring plugin for dependency injection or the Hibernate plugin for object-relational mapping. Struts also allows you to use different client-side technologies such as Jakarta Server Pages to build the frontend of your application.
Source: raygun.com
10 Best Java Frameworks You Should Know
Followed by Struts Framework, the next leading framework currently being used in the IT industry is the Wicket.

Social recommendations and mentions

Based on our record, Keras seems to be a lot more popular than Apache Struts. While we know about 35 links to Keras, we've tracked only 2 mentions of Apache Struts. 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 / over 1 year 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 / almost 2 years 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 / almost 2 years 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 2 years 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 / over 2 years ago
View more

Apache Struts mentions (2)

What are some alternatives?

When comparing Keras and Apache Struts, 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.

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.

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

Grails - An Open Source, full stack, web application framework for the JVM

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

Spark Mail - Spark helps you take your inbox under control. Instantly see what’s important and quickly clean up the rest. Spark for Teams allows you to create, discuss, and share email with your colleagues