Software Alternatives, Accelerators & Startups

Google Forms VS Keras

Compare Google Forms VS Keras and see what are their differences

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Google Forms logo Google Forms

Simple web forms from Google.

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.
  • Google Forms Landing page
    Landing page //
    2022-01-31
  • Keras Landing page
    Landing page //
    2023-10-16

Google Forms features and specs

  • User-Friendly Interface
    Google Forms offers a simple and intuitive interface, making it easy for users of all skill levels to create forms quickly.
  • Integration with Google Sheets
    Responses collected through Google Forms can be automatically sent to Google Sheets, facilitating data analysis and record-keeping.
  • Templates
    Google Forms provides a variety of pre-built templates that can be used as a starting point, saving time on form creation.
  • Collaboration Features
    Multiple users can collaborate in real-time on the creation and editing of forms, enhancing teamwork and productivity.
  • Free to Use
    Google Forms is free to use, making it an accessible tool for individuals and organizations without budget constraints.
  • Conditional Logic
    Supports conditional logic (skipping logic), allowing the form to change based on user responses.
  • Customization Options
    Users can customize the appearance of forms with themes, colors, and images to match their brand or personal style.
  • Accessibility and Mobile-Friendly
    Forms are responsive and can be accessed on various devices, including smartphones and tablets.

Possible disadvantages of Google Forms

  • Limited Customization
    While Google Forms offers basic customization, there are limitations in comparison to paid survey tools that allow for more advanced design capabilities.
  • Functionality for Advanced Data Collection
    Google Forms may lack some advanced data collection features such as advanced branching logic and question piping that are available in premium survey tools.
  • Limited Response Types
    Although it supports a variety of question types, it may not cover all niche functionality needs, such as certain interactive question formats.
  • Privacy Concerns
    As with any Google product, there may be concerns regarding data privacy and security, especially for sensitive information.
  • No Offline Access
    Google Forms requires an internet connection to create and respond to forms, limiting its use in offline environments.
  • Email Login Required
    Respondents may need to sign in with a Google account to complete certain forms, which can be a barrier for some users.
  • Limited Reporting Tools
    The built-in reporting features are basic, and users may need to export data to other tools for more in-depth analysis.

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 TensorFlowโ€™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 Google Forms

Overall verdict

  • Yes, Google Forms is generally considered good, especially for individuals or organizations looking for a straightforward and effective way to gather information and feedback. It is reliable, user-friendly, and offers sufficient features for most basic to intermediate needs.

Why this product is good

  • Google Forms is a popular tool due to its ease of use, intuitive interface, and seamless integration with other Google services. It allows users to quickly create surveys, quizzes, and forms without needing advanced technical skills. The tool is accessible from any device with internet access, making it convenient for users on the go. Furthermore, it offers a variety of question types, customizable templates, and real-time response collection and analysis, which enhances its functionality.

Recommended for

  • Educators for quizzes and surveys in classrooms
  • Businesses for gathering customer feedback
  • Event planners to collect RSVPs and preferences
  • Researchers conducting simple surveys
  • HR teams for internal feedback and employee satisfaction surveys

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

Google Forms videos

Review Google Forms responses

More videos:

  • Tutorial - Google Forms Full Tutorial From Start To Finish - How To Use Google Forms
  • Review - A tour of Google Forms

Keras videos

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 Google Forms and Keras)
Forms And Surveys
100 100%
0% 0
Data Science And Machine Learning
Surveys
100 100%
0% 0
OCR
0 0%
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 Google Forms and Keras

Google Forms Reviews

  1. Very convenient software!

    Helps my company solve many issues. We collect information from clients and employees. We conduct surveys and collect data. Very useful software. Helps form a common opinion, conduct analysis and analytics.

    ๐Ÿ Competitors: Survio
    ๐Ÿ‘ Pros:    Speed|Visual|Functionality
  2. โœ“ Adrian | Mobile Forms - Digital Inspections - Enterprise Checklists - Data collection
    ยท Marketing at Mobile Forms ยท
    A good beginners tool to start your digital transformation.

    One of our customers said: Our small mining operation needed to go from paper based process to digital forms. At first, Google forms allowed us to use this Web-based platform that lets individuals and businesses of all sizes build customizable forms to conduct surveys and generate real-time response charts.

    We saw that a small sample of our field workers quickly adopted the new way of working.

    Step 1: accomplished.

    Now unto step 2.

    How do we deploy this unto our whole team? We needed email notifications, offline response collection when without wifi on the field. Our CIO and his director of operations needed deep data and trends analysis as well. Our inspectors, when doing their audits, needed to capture approx. 25 high definition pictures, some audio notes and a video which wasn't really possible with google forms.

    So, we can 100% credit the use of google forms to our transition towards a paperless process, but as we navigated saashub.com a little more, we were able to discover a world of alternatives. We strongly suggest to start using google forms before undergoing a big implementation plan towards such enterprise level inspection tools like nspek or even cheaper solutions like prontoforms.

    I am not sure if we would start with google's solution first if we would to do this digital transformation all over, but it did allow us to discover it's limits pretty quickly.

    At some point, we needed custom fields and functions, and none of us was able to code, so the nSpek training that comes with the application definitely sets it's self apart, giving us full autonomy.

    ๐Ÿ Competitors: nSpek, ProntoForms
    ๐Ÿ‘ Pros:    No sign up cost
    ๐Ÿ‘Ž Cons:    Customization|Customer support|Data protection and security|No video|No pictures

10 SurveyMonkey Alternatives and Competitors in 2024
Google Forms is a user-friendly platform that allows you to create forms effortlessly. With its intuitive interface, you can select from various question types, customize the design, and add logic for a seamless customer experience throughout.
Source: clickup.com
9 Survey Monkey Alternatives for Your 2024 Market Research
Google Forms will be your choice if youโ€™re looking for a straightforward tool to create surveys without all the fuss. Itโ€™s particularly good for anyone who needs to whip up quick polls or surveys with a clean, user-friendly interface.
12 Easy Test Maker Alternatives
Google Forms is a Google Suite tool that comes with Google Drive. Users may quickly develop quizzes and get the results instantly, thanks to its simple and easy design
Alternatives to Deferendum
SurveyMonkey and Google Forms: These survey tools are designed for collecting feedback and data, whereas Deferendum is focused on group decision-making. Deferendum allows members to not only voice their opinions but also participate in the decision-making process and vote on proposed solutions.
Source: deferendum.com
Typeform Alternatives: Tools for Surveys, Forms, and Quizzes
Overall, online reviews suggest Typeform is like a paid version of Google Forms that doesnโ€™t provide any benefits over the free tool. Moreover, Google Forms does not have a response limit, while that is Typeforms most prominent criticism.
Source: survicate.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 Franรงois 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...

Social recommendations and mentions

Based on our record, Keras seems to be more popular. 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.

Google Forms mentions (0)

We have not tracked any mentions of Google Forms yet. Tracking of Google Forms recommendations started around Mar 2021.

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 runningโ€”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
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What are some alternatives?

When comparing Google Forms and Keras, you can also consider the following products

Survey Monkey - Create and publish online surveys in minutes, and view results graphically and in real time. SurveyMonkey provides free online questionnaire and survey software.

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.

Typeform - Create beautiful, next-generation online forms with Typeform, the form & survey builder that makes asking questions easy & human on any device. Try it FREE!

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

Jotform - Free Online Form Builder & Form Creator

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