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Crowdin VS TensorFlow

Compare Crowdin VS TensorFlow and see what are their differences

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Crowdin logo Crowdin

Localize your product in a seamless way

TensorFlow logo 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.
Not present

Crowdin is an AI-powered localization software for teams. Connect with over 600 tools to translate your content. Manage all your multilingual content in one place. Get quality translations for your app, website, game, supporting documentation, and so on. Invite your own translation team or work with professional translation agencies within Crowdin.

Key features include:

-Integration with 600+ apps, including Git, marketing, support, and other tools.

-Get translations from Crowdin language services, agencies from the marketplace, or your own translation team.

-Content integrations with GitHub, GitLab, Bitbucket, and Azure Repos.

-Integrations with Google Play, Android Studio, VS Code, and other systems.

-iOS and Android SDKs for over-the-air content delivery, real-time preview, and screenshots.

-Figma, Adobe XD, and Sketch plugins.

-Integrations with marketing tools: Mailchimp, Contentful, SendGrid, Hubspot, Dropbox, and more.

-API, CLI, webhooks.

-Translation Memory, Screenshots, In-Context Visual Editor, Machine Translations, Quality Assurance checks, Reports, and a Marketplace.

-Tasks and more.

For more information, visit crowdin.com. For enterprise businesses, try Crowdin for Enterprise: https://crowdin.com/enterprise

Crowdin supports more than 60 file formats for mobile, software, documents, subtitles, graphics and assets: .xml, .strings, .json, .html, .xliff, .csv, .php, .resx, .yaml, .xml, .properties, .strings, and so on.

  • TensorFlow Landing page
    Landing page //
    2023-06-19

Crowdin features and specs

  • Source Files Management
    Support of all popular file formats, files prioritization, export options, file revisions with a rollback possibility.
  • Over-The-Air Content Delivery
    An API to distribute and deliver translated content to the end users. Can be used with Crowdin Android and iOS SDK
  • Sketch Plugin
    Automate translation of content on your pages and artboards into multiple languages. Quickly generate language-specific assets.
  • Jira Integration
    Keep track of issues in the source strings reported by users working on the project translation. Each new issue in Crowdin becomes a sub-task in Jira automatically.
  • Translation memory
    Translation Memory (TM) is the vault of previously translated content from a particular project.
  • Google Play Integration
    Crowdin’s integration with Google Play improves the process of your app’s data localization.
  • GitHub, Bitbucket and GitLab Integrations
    Keep files synchronized between your repository in version control system and project in Crowdin.

TensorFlow features and specs

  • Comprehensive Ecosystem
    TensorFlow offers a complete ecosystem for end-to-end machine learning, covering everything from data preprocessing, model building, training, and deployment to production.
  • Community and Support
    TensorFlow boasts a large and active community, as well as extensive documentation and tutorials, making it easier for beginners to learn and experts to get help.
  • Flexibility
    TensorFlow supports a wide range of platforms such as CPUs, GPUs, TPUs, mobile devices, and embedded systems, providing flexibility depending on the user's needs.
  • Integrations
    TensorFlow integrates well with other Google products and services, including Google Cloud, facilitating seamless deployment and scaling.
  • Versatility
    TensorFlow can be used for a wide range of applications from simple neural networks to more complex projects, including deep learning and artificial intelligence research.

Possible disadvantages of TensorFlow

  • Complexity
    TensorFlow can be challenging to learn due to its complexity and the steep learning curve, particularly for beginners.
  • Performance Overhead
    Although TensorFlow is powerful, it can sometimes exhibit performance overhead compared to other, lighter frameworks, leading to longer training times.
  • Verbose Syntax
    The code in TensorFlow tends to be more verbose and less intuitive, which can make writing and debugging code more cumbersome relative to other frameworks like PyTorch.
  • Compatibility Issues
    Frequent updates and changes can lead to compatibility issues, requiring significant effort to keep libraries and dependencies up to date.
  • Mobile Deployment
    While TensorFlow supports mobile deployment, it is less optimized for mobile platforms compared to some other specialized frameworks, leading to potential performance drawbacks.

Analysis of Crowdin

Overall verdict

  • Crowdin is generally regarded as a good tool for localization management, particularly for businesses seeking to efficiently manage multilingual projects. The combination of robust features, ease of use, and integration options makes it a popular choice among developers and managers.

Why this product is good

  • Crowdin is considered a reliable platform for localization management due to its user-friendly interface and comprehensive features. It supports a wide range of file formats, offers real-time collaboration, and integrates with various tools and platforms. Its automated workflows and machine translation capabilities facilitate efficient translation processes. The platform is designed to streamline project management, making it easier for teams of all sizes to manage their localization needs.

Recommended for

    Crowdin is recommended for software developers, project managers, and localization teams working on apps, websites, or any digital product that demands efficient and effective translation management. It is also suitable for companies looking to expand their products' reach into international markets.

Crowdin videos

+ Add

Unlock New Features of Crowdin AI

More videos:

  • Demo - What's Crowdin?
  • Demo - Crowdin Apps & Integrations: a single tool to localize all your content
  • Tutorial - How To Manage Translations For Your Application | Crowdin & GitHub Tutorial

TensorFlow videos

+ Add

What is Tensorflow? - Learn Tensorflow for Machine Learning and Neural Networks

More videos:

  • Tutorial - TensorFlow In 10 Minutes | TensorFlow Tutorial For Beginners | Deep Learning & TensorFlow | Edureka
  • Review - TensorFlow in 5 Minutes (tutorial)

Category Popularity

0-100% (relative to Crowdin and TensorFlow)

Crowdin

TensorFlow

Localization
100 100%
Localization
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Website Localization
100 100%
Website Localization
0% 0
AI
0 0%
AI
100% 100

User comments

Share your experience with using Crowdin and TensorFlow. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Crowdin and TensorFlow

Crowdin Reviews

We have no reviews of Crowdin yet.
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TensorFlow Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
Source: www.labellerr.com
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
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks such as machine learning, computer vision, and natural language processing. It provides excellent support for deep learning models and is widely used in several industries. TensorFlow offers several pre-trained models for image classification, object detection,...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
There are a couple of notable exceptions to this rule, the most notable being that those in Reinforcement Learning should consider using TensorFlow. TensorFlow has a native Agents library for Reinforcement Learning, and Deepmind’s Acme framework is implemented in TensorFlow. OpenAI’s Baselines model repository is also implemented in TensorFlow, although OpenAI’s Gym can be...
Source: www.assemblyai.com

Social recommendations and mentions

Based on our record, Crowdin should be more popular than TensorFlow. It has been mentiond 22 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.

Crowdin mentions (22)

  • Tools to Automate GitHub Projects
    Crowdin simplifies translation management by syncing translations from GitHub to its dashboard. Translators can contribute without interacting with GitHub directly. Learn more about Crowdin here. - Source: dev.to / 3 months ago
  • What is Website Localization?
    There are many products out there such as Lokalize, Crowdin, Weglot, Adobe Target, etc can be used to achieve these experiences. Diving into the details and the general working of these products is out of scope of this blog post. But do give these products a try. - Source: dev.to / 7 months ago
  • How to Translate Your Next.js App in 5 Minutes With Crowdin
    We decided to see if there are any solutions to this issue on the market, did a bit of research, and decided to try out Crowdin - and we think it’s awesome! It offers:. - Source: dev.to / 10 months ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Crowdin.com — Unlimited projects, unlimited strings, and collaborators for Open Source. - Source: dev.to / over 1 year ago
  • Coding for UX writers
    We're using Crowdin for this, since we need to localise with external partners to different languages: https://crowdin.com/. But there are other options on the market that are geared more towards providing a true source of text, like Frontitude or Ditto: Https://www.frontitude.com/ Https://www.dittowords.com/. Source: over 1 year ago
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TensorFlow mentions (7)

  • Creating Image Frames from Videos for Deep Learning Models
    Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / over 2 years ago
  • Need help with a Tensorflow function
    So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 3 years ago
  • Help: Slow performance with windows 10 compared to Ubuntu 20.04 with TF2.7
    Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 3 years ago
  • [Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
    I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 3 years ago
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What are some alternatives?

When comparing Crowdin and TensorFlow, you can also consider the following products

Transifex - Transifex makes it easy to collect, translate and deliver digital content, web and mobile apps in multiple languages. Localization for agile teams.

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

Lokalise - Localization tool for software developers. Web-based collaborative multi-platform editor, API/CLI, numerous plugins, iOS and Android SDK.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

POEditor - The translation and localization management platform that's easy to use *and* affordable!

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

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