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Keras VS Netlify

Compare Keras VS Netlify 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.

Netlify logo Netlify

Build, deploy and host your static site or app with a drag and drop interface and automatic delpoys from GitHub or Bitbucket
  • Keras Landing page
    Landing page //
    2023-10-16
  • Netlify Landing page
    Landing page //
    2023-10-23

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.

Netlify features and specs

  • Deployment Speed
    Netlify offers very fast and easy deployment processes, often requiring just a push to a Git repository.
  • Built-in CDN
    Netlify includes a global Content Delivery Network (CDN) to speed up the delivery of websites and applications.
  • Serverless Functions
    Netlify provides serverless functions allowing developers to run backend code without managing servers.
  • Automated Builds
    Automated build processes are integrated, supporting continuous integration and deployment (CI/CD).
  • Custom Domains and SSL
    Easily manage custom domains and automatically provision and renew SSL certificates.
  • Integrated Form Handling
    Netlify offers form handling capabilities out-of-the-box, simplifying the process of collecting form data.
  • Plugins and Integrations
    Extensible with a wide range of plugins and integrations including analytics, CMS, and other third-party services.
  • Developer-Friendly
    Offers a wide range of developer-friendly features, such as split testing, instant rollbacks, and APIs for customization.
  • Free Tier
    Generous free tier that allows for hosting of personal projects and small websites at no cost.

Possible disadvantages of Netlify

  • Pricing
    While there's a free tier, more advanced features and higher usage can become expensive on a paid plan.
  • Function Limits
    Serverless functions have execution and duration limits, which may not be suitable for all applications.
  • Platform-Specific
    Deployment and feature configurations can be platform-specific, which may require learning new processes that differ from other providers.
  • Build Minutes
    The free tier includes limited build minutes, which can be a constraint for projects that require frequent deployments.
  • Vendor Lock-In
    Using Netlify-specific features (like certain build plugins) can make it harder to migrate to another hosting provider.
  • Limited Backend Services
    Primarily designed for frontend applications, so it may not be as robust for extensive backend services compared to traditional servers.
  • Steep Learning Curve
    Some advanced features may have a steep learning curve for beginners.
  • Build Times
    Build times can be slow for very large sites or monorepos, impacting continuous deployment speed.
  • Support
    Customer support responses can be slow on the lower-tier plans.

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 Netlify

Overall verdict

  • Netlify is considered a good option for many developers and businesses looking for a platform to deploy and manage static websites or Jamstack applications.

Why this product is good

  • Netlify offers a seamless and easy-to-use platform for deploying static sites and modern web applications.
  • It provides developers with a variety of powerful features like continuous deployment, built-in HTTPS, DNS management, and serverless functions.
  • The platform supports server-side rendering and dynamic functions, which is advantageous for modern web development needs.
  • Netlify's workflow optimizes for Git, allowing developers to connect their repositories directly and automate deployment processes.
  • The platform's collaboration tools make it easy for teams to work together on website development.

Recommended for

  • Developers building static sites or Jamstack applications.
  • Teams looking for streamlined deployment workflows integrated with Git providers.
  • Businesses seeking a robust hosting solution with minimal server management overhead.
  • Projects requiring custom domains with automatic HTTPS.

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

Netlify videos

+ Add

Netlify Platform Tutorial Review

More videos:

  • Review - Deploy Websites In Seconds With Netlify
  • Review - Deploy Your Website In Minutes With Netlify

Category Popularity

0-100% (relative to Keras and Netlify)

Keras

Netlify

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Cloud Computing
0 0%
Cloud Computing
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Developer Tools
0 0%
Developer 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 Keras and Netlify

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

Netlify Reviews

  1. Eleanor Bennett
    · Digital Marketing Specialist at Logit.io ·
    Useful previews

    As someone who is often creating new pages, Netlify's preview makes the review process easier. You can also use the generated URL from Netlify's preview to run an SEO audit prior to going live. This is very useful for spotting bugs or broken redirects.

Top 15 Cloudflare Alternatives: A Complete Guide
Netlify is a CDN service that also offers edge computing, web security, and VPN solutions. Netlify allows you to deploy and run your web content and applications on its edge network, which has over 70 edge locations in 35 countries. Netlify also provides security features, such as SSL, DDoS protection, WAF, and firewall, to protect your web content and applications.
Source: www.theknowledgeacademy.com
Exploring alternatives to Vercel: A guide for web developers
Netlify is one of the most popular alternatives to Vercel, offering a comprehensive platform for deploying static sites and modern web applications. With a strong focus on developer experience, Netlify provides powerful features such as serverless functions, continuous deployment, and advanced analytics.
Source: fleek.xyz
Choosing the best Next.js hosting platform
Where Netlify is superior to Vercel is the list of add-ons they offer. Among them, Netlify Forms allow developers to manage forms and submission without extra code. It even integrates with third-party applications such as MailChimp, Zendesk, and more.
Source: blog.logrocket.com
Top 10 Netlify Alternatives
Although Netlify is a credible static app hosting and deployment platform for all sizes of businesses. But if you still want alternatives, then you should consider our suggested Netlify alternatives. This guide displays all these alternatives to Netlify in detail with pricing structure and core properties. Hopefully, you will pick a suitable option for your project.
Source: blog.back4app.com
3 best alternatives to the big cloud providers
Very interesting topic! I’m not sure if things like Netlify or Vercel could replace something like Kubernetes on GCP but I believe in the power of Netlify for hosting websites!
Source: dev.to

Social recommendations and mentions

Based on our record, Netlify should be more popular than Keras. It has been mentiond 109 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
View more

Netlify mentions (109)

  • Build a Personal Portfolio Website (2-Minute Tutorial)
    Upload your folder to Netlify, GitHub Pages, or Vercel — and boom, your portfolio is online! - Source: dev.to / about 1 month ago
  • Deploy Your Full-Stack App for Free: Host Backend on Render and Frontend on Netlify in Minutes
    Deploy on Netlify Go to https://netlify.com and log in. Click "Add new site" → "Import an existing project". Connect your GitHub and choose your frontend repo. Fill in the deploy settings: Build Command: npm run build (or flutter build web) Publish Directory: build (for React) or build/web (for Flutter) Add your environment variables (e.g., your backend URL). Click Deploy Site. You’ll get a public frontend URL like:. - Source: dev.to / about 2 months ago
  • How Bun can help to revive a Gridsome project
    Starting from this year, builds for this website's code through my Netlify account began failing. - Source: dev.to / 3 months ago
  • I'm Joining Sentry
    As much as this is exciting news, it does mean that sadly I'm moving on from Netlify. Netlify which has been my home for the last 2 years and who believed in us(and me) before anyone else did. Their support is what made SolidStart possible. I've learned so much about deployment and infrastructure working closely with the Frameworks and Primitives team. I've traveled the world giving talks alongside the Developer... - Source: dev.to / 10 months ago
  • Join us for the Netlify Dynamic Site Challenge: $3,000 in Prizes!
    We are so excited to team up with Netlify to bring you our next DEV challenge. This Challenge is all about dynamic and high-performance digital experiences, across any framework! - Source: dev.to / about 1 year ago
View more

What are some alternatives?

When comparing Keras and Netlify, 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.

Vercel - Vercel is the platform for frontend developers, providing the speed and reliability innovators need to create at the moment of inspiration.

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

CloudFlare - Cloudflare is a global network designed to make everything you connect to the Internet secure, private, fast, and reliable.

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

Heroku - Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.

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