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Zapier VS Keras

Compare Zapier VS Keras and see what are their differences

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Zapier logo Zapier

Connect the apps you use everyday to automate your work and be more productive. 1000+ apps and easy integrations - get started in minutes.

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.
  • Zapier Landing page
    Landing page //
    2023-07-24
  • Keras Landing page
    Landing page //
    2023-10-16

Zapier features and specs

  • Ease of Use
    Zapier offers an intuitive interface, making it easy for non-technical users to set up automated workflows without any coding knowledge.
  • Wide Range of Integrations
    With support for over 3,000 apps, Zapier allows you to connect a multitude of platforms and services, facilitating robust and diverse automation opportunities.
  • Custom Automation
    Users can create customized automation workflows (Zaps) tailored to their specific business needs, enhancing productivity and efficiency.
  • Scalability
    Zapier can handle both simple tasks and complex, multi-step workflows, making it suitable for businesses of any size.
  • Excellent Support and Resources
    Zapier offers extensive documentation, tutorials, and customer support to help users get the most out of its platform.
  • No Startup Costs
    Zapier offers a free tier, which is suitable for basic use cases or for testing the platform before committing to a paid plan.
  • Time-Saving
    By automating repetitive tasks, Zapier saves users considerable time, allowing them to focus on more strategic activities.

Possible disadvantages of Zapier

  • Cost
    Advanced functionalities and higher task volumes are only available on paid plans, which can be expensive for small businesses.
  • Limited by API
    Zapier's capabilities are constrained by the APIs of the apps it integrates with, meaning it can't perform functions outside of what the app's API supports.
  • Task Limitations
    The free plan has a limit on the number of tasks (automations) you can perform per month, which may not be sufficient for heavy users.
  • Complex Workflows Require Expertise
    While simple tasks are easy to set up, more complex workflows can require a good understanding of how APIs and integrations work, which may necessitate expert knowledge.
  • Performance Variability
    The speed at which Zaps execute can vary depending on the load on Zapier's servers and the response times of integrated apps.
  • Data Privacy
    Storing workflow data in a third-party platform may raise data privacy and security concerns, especially for businesses handling sensitive information.
  • Customization Limitations
    While Zapier is highly customizable, it may not offer the same level of customization and flexibility as custom-built solutions tailored entirely to unique business processes.

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 Zapier

Overall verdict

  • Yes, Zapier is generally considered a good tool for automating tasks across different applications. Its reliability, ease of use, and broad integration capabilities make it a valuable asset for individuals and businesses looking to enhance productivity.

Why this product is good

  • Zapier is a popular automation tool that allows users to connect various apps and services to automate repetitive tasks. It supports a wide range of applications and offers a user-friendly interface, making it accessible even for non-technical users. The platform is known for its extensive library of integrations, flexibility, and efficiency in streamlining workflows.

Recommended for

  • Small to medium-sized businesses looking to automate processes and integrate multiple applications.
  • Freelancers or individuals seeking to streamline their workflows without extensive technical skills.
  • Teams looking to reduce manual, repetitive tasks and improve operational efficiency.

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

Zapier videos

+ Add

Zapier Developer Platform Example Etsy

More videos:

  • Tutorial - Zapier Tutorial | How to Automate Tasks and STOP WASTING TIME!
  • Review - A COMPLETE GUIDE TO USING ZAPIER - Beginner's Edition
  • Review - Getting started with Zapier triggers and actions
  • Review - What is Zapier?
  • Tutorial - Zapier 2022 Automation Review & Tutorial - How To Make A Zap 🤖

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 Zapier and Keras)

Zapier

Keras

Web Service Automation
100 100%
Web Service Automation
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Automation
100 100%
Automation
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 Zapier and Keras

Zapier Reviews

The Best n8n.io Alternatives for Workflow Automation in 2025
Zapier is a widely-used workflow automation tool that has gained popularity due to its user-friendly interface and extensive library of pre-built integrations. It enables users to create "Zaps," which are essentially automated workflows that connect different applications and services, without the need for coding. Zapier's strengths lie in its simplicity and the sheer number...
Source: latenode.com
N8n.io Alternatives
Zapier is a powerful automation tool that connects your favorite apps and services, streamlining workflows and increasing productivity. With Zapier, you can automate repetitive tasks without needing any coding skills, making it accessible for users of all technical levels.
Source: apix-drive.com
The Best MuleSoft Alternatives [2024]
Zapier is a reliable MuleSoft alternative because it allows users to automate workflows and connect systems to interact with and share data between 6,000+ apps.
Source: exalate.com
Top 5 Microsoft Power Automate alternatives for 2024
“Zapier is a great option among Power Automate alternatives,” says Kev Tilley, financial expert and managing director at Mortgageable UK. “Like Power Automate, Zapier has a wide range of built-in integrations that make it easy to connect to popular apps and services. In addition, Zapier offers support for custom connectors.”
Source: www.jotform.com
Top 15 MuleSoft Competitors and Alternatives
Zapier is a software company specializing in task automation. Businesses can use Zapier to integrate web applications and automate workflows. In 2022, Zapier enabled customers to connect and move data across over 5,000 apps, including Salesforce, Jira, and Airtable.
Source: bstrategyhub.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

Keras might be a bit more popular than Zapier. We know about 35 links to it since March 2021 and only 27 links to Zapier. 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.

Zapier mentions (27)

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 / 7 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 / 12 months 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 Zapier and Keras, you can also consider the following products

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

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.

Make.com - Tool for workflow automation (Former Integromat)

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

n8n.io - Free and open fair-code licensed node based Workflow Automation Tool. Easily automate tasks across different services.

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

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