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Keras VS Codeception

Compare Keras VS Codeception 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.

Codeception logo Codeception

Codeception is a new full-stack testing PHP framework.
  • Keras Landing page
    Landing page //
    2023-10-16
  • Codeception Landing page
    Landing page //
    2022-08-03

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.

Codeception features and specs

  • Unified Testing Framework
    Codeception allows you to write tests for unit, functional, and acceptance testing in one framework, offering a consistent interface and reducing the need to switch between tools.
  • BDD Support
    Codeception supports Behavior Driven Development (BDD) which enables writing human-readable test scenarios, making it easier for non-developers to understand test cases.
  • Modular Architecture
    Codeception’s modular architecture makes it highly extensible and customizable, allowing the reuse of modules and integration with popular frameworks like Symfony, Laravel, and Yii.
  • Comprehensive Suite of Helpers
    It offers a wide range of helper modules for various tasks and integrations, such as interacting with web pages and SOAP/REST APIs, which simplifies the setup of tests.
  • Active Community and Documentation
    Codeception has an active community and comprehensive documentation, which provides support and examples for most use cases.

Possible disadvantages of Codeception

  • Complex Setup for Beginners
    The flexibility and feature set of Codeception might be overwhelming for newcomers, requiring more time to understand and correctly set up the environment.
  • Steep Learning Curve
    Codeception’s comprehensive range of functionalities and modularity may result in a steeper learning curve compared to simpler testing frameworks.
  • Overhead for Small Projects
    For small projects, Codeception might be an overkill due to its complex configuration and multitude of features, which might not all be needed.
  • Heavy Dependency on PHP
    As Codeception is a PHP-based testing framework, teams using multiple languages or technologies might require separate solutions for non-PHP environments.
  • Performance Overhead
    Running complete acceptance tests through browsers can lead to performance overhead, especially for large test suites, possibly requiring more infrastructure and time.

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

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

Codeception videos

+ Add

Our First Acceptance Test [6/24] Codeception & Symfony2

More videos:

  • Tutorial - How to Run Codeception Tests [5/24] Codeception & Symfony2
  • Review - Bootstrapping Codeception [2/24] Codeception & Symfony2

Category Popularity

0-100% (relative to Keras and Codeception)

Keras

Codeception

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Automated Testing
0 0%
Automated Testing
100% 100
OCR
100 100%
OCR
0% 0
Browser Testing
0 0%
Browser Testing
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 Codeception

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

Codeception Reviews

We have no reviews of Codeception yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Keras should be more popular than Codeception. 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.

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

Codeception mentions (8)

  • Any pro-tips for writing automated tests with Selenium PHP?
    Personal experience: - don’t use Behat unless you really needed a “story telling”, it has a intermediate layer Gherkin that you’ll need to code. You can write “Given/When/Then” steps but you’ll also need to write “php code” that will interpret this step. - using real browser be prepared for instability - any interaction with JavaScript can broken/delay execution - be prepared that this tests are call functional... Source: over 3 years ago
  • PHPUnit, do i need to learn it?
    Codeception: https://codeception.com/. Source: over 3 years ago
  • Advice for an older symfony 4.4 project
    I would say to check out Codeception. Codeceptions has modules for Symfony and database generally. Long and short of it is that if you want you can run api tests that go into the controllers and rollback the database afterwards. Source: almost 4 years ago
  • Automating Tests using CodeceptJS and Testomat.io: First Steps
    There are enough blog posts about Jest or Cypress already, so let me introduce Codecept. It comes in two flavors. There is Codeception for PHP, and there is CodeceptJS for JavaScript which we will be using here. - Source: dev.to / about 4 years ago
  • Testing PHP Applications
    There are many tools you can use for this purpose, but one I particularly like is CodeCeption. What I like most about it is that it's a unified tool that can be used to perform several types of tests, acceptance being one of them. - Source: dev.to / about 4 years ago
View more

What are some alternatives?

When comparing Keras and Codeception, 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.

PHPUnit - Application and Data, Build, Test, Deploy, and Testing Frameworks

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

TestMu AI (Formerly LambdaTest) - World’s first full-stack Agentic AI Quality Engineering platform.

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

CrossBrowserTesting - Browser Testing made simple! Run automated, visual, and manual tests on 1500+ real browsers and mobile devices. Test more browsers, in less time.

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