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Keras VS OverAPI

Compare Keras VS OverAPI and see what are their differences

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  3. » Reviews
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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.

OverAPI logo OverAPI

Largest cheat sheet for programming languages and libraries
  • Keras Landing page
    Landing page //
    2023-10-16
  • OverAPI Landing page
    Landing page //
    2020-02-03

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.

OverAPI features and specs

  • Comprehensive Resource
    OverAPI compiles a wide range of cheat sheets for different programming languages and technologies, providing a one-stop resource for developers needing quick reference material.
  • User-Friendliness
    The website's layout is straightforward and categorized by technology, making it easy for users to find the specific cheat sheets they need.
  • Time Efficiency
    By offering quick access to essential information, OverAPI helps developers save time that would otherwise be spent searching through documentation or other sources.
  • Free Access
    All the resources on OverAPI are freely available, making it an accessible tool for developers at all levels without any cost barrier.

Possible disadvantages of OverAPI

  • Limited Interaction
    OverAPI primarily serves as a static list of cheat sheets and does not provide interactive learning or problem-solving features.
  • Potential Outdated Information
    Some cheat sheets may not be regularly updated, leading to the possibility of encountering outdated information as programming languages and tools evolve.
  • Dependency on External Sources
    Since OverAPI compiles resources from various sources, users might encounter varying formats and quality of information, depending on the original source.
  • Lack of Depth
    While useful for quick references, cheat sheets often provide limited explanations and may not suffice for users seeking in-depth understanding of a topic.

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

OverAPI videos

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OverAPI Collecting All Cheat Sheets - Review

Category Popularity

0-100% (relative to Keras and OverAPI)

Keras

OverAPI

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Design Tools
0 0%
Design Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Productivity
0 0%
Productivity
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 OverAPI

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

OverAPI Reviews

We have no reviews of OverAPI yet.
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Social recommendations and mentions

Based on our record, Keras should be more popular than OverAPI. 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 / about 2 months 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
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OverAPI mentions (11)

  • 100+ FREE Resources Every Web Developer Must Try
    . HTML Cheat Sheet: Quick reference guide for HTML elements and attributes. . CSS Cheat Sheet: Comprehensive guide to CSS properties and selectors. . JavaScript Cheat Sheet: Handy reference for JavaScript syntax and concepts. . Git Cheat Sheet: Essential commands and workflows for Git. . Markdown Cheat Sheet: Markdown syntax guide for creating rich text formatting. . React Cheat Sheet: Quick overview of React... - Source: dev.to / 11 months ago
  • 2024 Cheat Sheet Collection
    OverAPI: OverAPI is a comprehensive hub that collects and curates cheat sheets for developers. It goes beyond just API-related content and serves as a centralized repository for cheat sheets covering a wide array of programming languages. From popular choices like Python, JavaScript, and Ruby to more niche languages, OverAPI has got you covered. - Source: dev.to / about 1 year ago
  • Useful Websites for Cheat Sheets and Programming Resources
    Content: OverAPI.com is a repository that compiles cheat sheets for various programming languages and technologies, including Python, jQuery, NodeJS, PHP, Java, and more. Benefits: It provides quick references and revision aids for a wide range of programming topics, making it an invaluable resource for programmers. Link: https://overapi.com/. - Source: dev.to / about 1 year ago
  • 19 Handy Websites for Web Developers
    A collection of cheat sheets for various programming languages and frameworks. - Source: dev.to / over 1 year ago
  • Best Websites For Coders
    Collecting all the cheat sheets : cheat sheets for lots of programming languages. - Source: dev.to / over 2 years ago
View more

What are some alternatives?

When comparing Keras and OverAPI, 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.

Devhints - TL;DR for developer documentation

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

DevDocs - Open source API documentation browser with instant fuzzy search, offline mode, keyboard shortcuts, and more

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

GitSheet - A dead simple Git cheat sheet.

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