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Keras VS TanStack Table

Compare Keras VS TanStack Table and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

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.

TanStack Table logo TanStack Table

Headless UI for building powerful tables & datagrids with TS/JS, React, Solid, Svelte and Vue
  • Keras Landing page
    Landing page //
    2023-10-16
  • TanStack Table Landing page
    Landing page //
    2023-09-03

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 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.

TanStack Table features and specs

  • Performance
    TanStack Table is designed for high performance, capable of handling large datasets efficiently through features like virtualized scrolling, which only renders visible rows.
  • Customization
    Provides extensive customization options for UI and behavior, allowing developers to tailor the table to specific needs with hooks and plugins.
  • Lightweight
    The core library is minimal and can be extended with plugins, making it lightweight by default and allowing developers to include only the features they need.
  • Headless Design
    Being headless, TanStack Table focuses solely on offering functionality, leaving the implementation of styles and appearance completely to the developer, which provides flexibility.
  • Community and Documentation
    The library has an active community and comprehensive documentation, which helps developers quickly understand and implement features.

Possible disadvantages of TanStack Table

  • Complexity
    With its headless nature and high level of customization, there can be a steep learning curve for developers unfamiliar with its approach or those new to React.
  • Lack of Built-in Styles
    Since it does not include built-in styles or components, additional work is required to implement design aspects, which may be a drawback for projects that need a quick setup.
  • React Dependency
    It is specifically designed for React, which makes it unsuitable for projects built with other frameworks.
  • Fragmentation
    Due to its plugin-based architecture, essential features can sometimes depend on third-party solutions, leading to possible fragmentation or inconsistency in updates and support.

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

TanStack Table videos

No TanStack Table videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Keras and TanStack Table)

Keras

TanStack Table

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
OCR
100 100%
OCR
0% 0
Design Tools
0 0%
Design 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 TanStack Table

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...
Source: searchbusinessanalytics.techtarget.com

TanStack Table Reviews

Using AG Grid in React: Guide and alternatives
Implementing pagination can be a little trickier. But one of the benefits of TanStack Table is that we have complete control over the functionality. Letโ€™s implement server-side pagination with TanStack Table and see how it works.
Source: blog.logrocket.com
The Best React Data Grid/Table Libraries with Material Design in 2023 - MRT Blog
The main advantage of this project is that it is also built on top of TanStack Table v8 (formerly known as React Table) and TanStack Virtual v3 (formerly known as React Virtual), which are powerful headless UI libraries for efficiently rendering react table components with virtualization. This also means the the APIs to customize the behavior of the table are standardized...
Source: www.material-react-table.com
Best Free and Open-Source JavaScript Data Grid Libraries and Widgets
The TanStack Table library is a modern and up-to-date library for creating powerful tables and data grids. This is actually a headless library, so it won't ship with components, markup, or styles.
Source: code.tutsplus.com

Social recommendations and mentions

Based on our record, Keras should be more popular than TanStack Table. 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 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 / over 1 year 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 / over 1 year 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 / about 2 years ago
View more

TanStack Table mentions (6)

  • Building a Google Sheetsโ€“Like Table Component with TanStack Table, Zod, and ShadCN/UI
    TanStack Table for the core table logic. - Source: dev.to / over 1 year ago
  • What are headless UI libraries?
    UI libraries aside, the whole headless rave has spread to packages and libraries for standalone components, headless text editors like Tiptap and Platejs, headless table components like Tanstack table, and more out there to explore. - Source: dev.to / over 2 years ago
  • Task tracker application using NextJS and SurrealDB
    To create the task table I have used [@tanstack/react-table](https://tanstack.com/table/v8) as it has many features like searching, pagination, sorting, and filtering. As it is a Headless table library it handles most of the complex tasks on its own. - Source: dev.to / over 2 years ago
  • React Ecosystem inย 2024
    If you're looking for information about tables in React, you can explore the TanStack Table documentation for version 8 at tanstack.com/table/v8. TanStack Table is a headless UI library that allows you to build powerful tables and datagrids in various frameworks like TS/JS, React, Vue, Solid, and Svelte while retaining control over markup and styles. The documentation will provide you with detailed information on... - Source: dev.to / over 2 years ago
  • โšก Best Open Source React framework and libraries for Building Enterprise B2B apps
    Refer to TanStack Table documentation. - Source: dev.to / almost 3 years ago
View more

What are some alternatives?

When comparing Keras and TanStack Table, 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.

AG Grid - The best HTML5 datagrid in the world

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

MUI X Data Grid - A fast and extensible React data table and React data grid, with filtering, sorting, aggregation, and more.

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

Mantine - React library, 60+ hooks and components with dark theme support and focus on accessibility

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