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Backbone.js VS Keras

Compare Backbone.js VS Keras and see what are their differences

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Backbone.js logo Backbone.js

Give your JS App some Backbone with Models, Views, Collections, and Events

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.
  • Backbone.js Landing page
    Landing page //
    2018-09-30
  • Keras Landing page
    Landing page //
    2023-10-16

Backbone.js features and specs

  • Lightweight
    Backbone.js is minimal and lightweight, which means it has a small footprint and adds very little overhead to your project.
  • Flexibility
    Backbone.js provides a flexible structure to developers by allowing them to build their own MVC or MVP architectures using models, views, collections, and routers.
  • Ease of Integration
    Backbone.js can be easily integrated with other libraries and frameworks, such as jQuery or underscore.js, enhancing its capabilities without much difficulty.
  • Large Community
    Backbone.js has been around for a long time, resulting in a large community and a plethora of plugins and extensions that can be leveraged.
  • Detailed Documentation
    The official site offers comprehensive documentation which includes tutorials, examples, and a detailed API reference, aiding developers to understand and utilize the library efficiently.

Possible disadvantages of Backbone.js

  • Steeper Learning Curve
    New developers might find Backbone.js difficult to learn due to its non-opinionated nature and lack of enforced structure.
  • Sparse In-Built Features
    Backbone.js provides only the basic building blocks, requiring developers to write more boilerplate code or rely on external libraries for additional functionalities.
  • Outdated
    As newer frameworks and libraries (like React, Vue, and Angular) have emerged with more robust features and better performance, Backbone.js has somewhat fallen out of favor in modern development practices.
  • Event Binding Complexity
    Managing event bindings in Backbone.js can become complex and sometimes messy in large applications, which can lead to difficult maintenance and debugging.
  • Limited Two-Way Data Binding
    Backbone.js does not provide two-way data binding out-of-the-box, unlike other frameworks such as Angular, necessitating additional code to sync views and models.

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 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

Backbone.js videos

+ Add

Introduction to Backbone.js

More videos:

  • Review - Introduction to Backbone.js
  • Review - Backbone.js Code Review w Backbone.js Mentor Jonathon

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

Category Popularity

0-100% (relative to Backbone.js and Keras)

Backbone.js

Keras

JavaScript Framework
100 100%
JavaScript Framework
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Javascript UI Libraries
100 100%
Javascript UI Libraries
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Backbone.js and Keras

Backbone.js Reviews

20 Next.js Alternatives Worth Considering
A veteran on the scene, Backbone.js is all about giving structure to your JavaScript-heavy applications. It’s standing the test of time, enabling you to keep your data logic and display logic neatly side by side, all while being lightweight.
Source: tms-outsource.com
9 Best JavaScript Frameworks to Use in 2023
Backbone.js is based on the Model View Controller (MVC) design pattern. The library supports seven components: Models, Views, Collections, Routers, Events, Sync, and Options. Backbone.js also provides an asynchronous communication layer that allows the application to communicate with a backend service.
Source: ninetailed.io
JavaScript: What Are The Most Used Frameworks For This Language?
Backbone.JS is a lightweight JavaScript library that provides a framework for developing structured and scalable web applications. It offers a set of tools for building client-side applications that interact with RESTful APIs. Backbone.JS is well-suited for developing single-page applications (SPAs) where most of the user interface is rendered in the browser, rather than...
Source: www.bocasay.com
20 Best JavaScript Frameworks For 2023
Backbone.js is a JavaScript-based framework that connects to an API via a RESTful JSON interface. Backbone.js is known for being small and light because it only requires jQuery and one JavaScript library, Underscore.js, to use the entire library.
Source: www.lambdatest.com
Top JavaScript Frameworks For Mobile App Development
Backbone JS is a JavaScript framework based on the MVP app design. As the name suggests, it acts as a strong backbone to your project. It is lightweight in nature and hence, is considered ideal for developing single-page applications. It offers a simplistic frontend and makes the best use of JavaScript functions.
Source: medium.com

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

Social recommendations and mentions

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

Backbone.js mentions (17)

  • JavaScript Views, the Hard Way – A Pattern for Writing UI
    Https://backbonejs.org/#View There is also a github repo that has examples of MVC patterns adapted to the web platform. - Source: Hacker News / about 2 months ago
  • JavaScript evolution: From Lodash and Underscore to vanilla
    Underscore was created by Jeremy Ashkenas (the creator of Backbone.js) in 2009 to provide a set of utility functions that JavaScript lacked at the time. It was also created to work with Backbone.js, but it slowly became a favorite among developers who needed utility functions that they could just call and get stuff done with without having to worry about the inner implementations and browser compatibility. - Source: dev.to / 6 months ago
  • React is 10 years old
    Got it thanks for the context. I've read the web app and it seems to me it is just https://backbonejs.org/ re-written in Typescript and allows JSX. I'm very certain Typescript and JSX will have improved the DX for Backbone like apps, but it doesn't address all of the other issues that teams had with Backbone. e.g. Cyclical event propagation, state stored in the DOM (i.e. Appendchild is error prone in large code... - Source: Hacker News / about 2 years ago
  • Just Simply – Stop saying how simple things are in our docs
    Even further nowadays, docs are created using Docusaurus. I don't have problem with it but documentation should be good (eye) friendly than easy to write. Why not be creative while writing docs such as - Backbone.js - https://backbonejs.org Or https://backbonejs.org/docs/backbone.html as code annotation. - Source: Hacker News / about 2 years ago
  • The Emperor's New Library
    What we see, a decade ago, are that many of the "popular" libraries, frameworks, and methods, not surprisingly, have gone by the wayside, a lot that have remained in current code as difficult-to-removemodernize legacy cruft (Bower, Gulp, Grunt, Backbone, Angular 1, ...), and then we have the small minority that are still here. Some that remain have had their utility lessened/questioned by platform and language... - Source: dev.to / over 2 years ago
View more

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

What are some alternatives?

When comparing Backbone.js and Keras, you can also consider the following products

AngularJS - AngularJS lets you extend HTML vocabulary for your application. The resulting environment is extraordinarily expressive, readable, and quick to develop.

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.

ExpressJS - Sinatra inspired web development framework for node.js -- insanely fast, flexible, and simple

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

ember.js - A JavaScript framework for creating ambitious web apps

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

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