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Invision VS PyTorch

Compare Invision VS PyTorch and see what are their differences

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Invision logo Invision

Prototyping and collaboration for design teams

PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...
  • Invision Landing page
    Landing page //
    2023-10-07
  • PyTorch Landing page
    Landing page //
    2023-07-15

Invision features and specs

  • Collaborative Features
    InVision provides a range of collaborative tools like real-time co-editing, feedback, and comments, which make it easier for teams to work together.
  • Prototyping
    InVision allows for high-fidelity, interactive prototypes that closely mimic the final product, helping stakeholders understand the user experience better.
  • Integrations
    The platform integrates seamlessly with other popular design tools such as Sketch, Photoshop, and various project management tools, enhancing workflow efficiency.
  • User Testing
    InVision supports user testing features that allow designers to gather real-time feedback from end-users, improving the final product's usability.
  • Version Control
    It offers robust version control features, allowing teams to track changes, revert to previous versions, and maintain an organized workflow.
  • Cloud Storage
    Cloud-based storage ensures that all project files are accessible from anywhere, making it convenient for remote teams.

Possible disadvantages of Invision

  • Learning Curve
    The platform can be complex for new users, requiring time to learn and fully understand its extensive features.
  • Performance Issues
    Some users have reported performance issues, particularly with large projects, which can slow down the workflow.
  • Cost
    InVision can be expensive, especially for small teams or freelancers, despite offering many valuable features.
  • Limited Offline Access
    Since it's a cloud-based tool, offline access to projects and files is limited, which can be an issue for teams with unreliable internet connections.
  • Mobile Experience
    The mobile experience is not as robust as the desktop version, which can be limiting for users who need to work on the go.

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

Analysis of PyTorch

Overall verdict

  • Yes, PyTorch is considered a good deep learning framework.

Why this product is good

  • Ease of Use: PyTorch has an intuitive interface that makes it easier to learn and use, especially for beginners.
  • Dynamic Computation Graphs: PyTorch employs dynamic computation graphs, which provide more flexibility in building and modifying models on the fly.
  • Strong Community and Support: PyTorch has a large and active community, offering extensive resources, forums, and tutorials.
  • Research Adoption: PyTorch is widely adopted in the research community, making state-of-the-art models and techniques readily available.
  • Integration: PyTorch integrates well with other libraries and tools in the Python ecosystem, providing robust support for various applications.

Recommended for

  • Researchers and Academics: Ideal for those who need a flexible and dynamic tool for experimenting with new models and techniques.
  • Industry Practitioners: Suitable for developers and data scientists working on production-level machine learning solutions.
  • Educators and Learners: Great for educational purposes due to its easy-to-understand syntax and comprehensive documentation.

Invision videos

+ Add

InVision Studio Review | Here's what we think!

More videos:

  • Review - Thoughts On InVision Studio
  • Review - Welcome to InVision Studio | Overview

PyTorch videos

+ Add

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Category Popularity

0-100% (relative to Invision and PyTorch)

Invision

PyTorch

Prototyping
100 100%
Prototyping
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Design Tools
100 100%
Design Tools
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 Invision and PyTorch

Invision Reviews

10 Best Figma Alternatives in 2024
A visual collaboration tool and best figma alternative called InVision enables communication between designers during many phases of product design, such as development, testing, and prototyping. It’s also used for UI and UX design.
Source: www.geeksforgeeks.org
9 Best InVision Alternatives to Switch to in 2024
On 4 January 2024, InVision announced that its design collaboration services are shutting down. So, we came up with nine InVision alternatives that you can switch to this year.
Source: designmodo.com
Figma Alternatives: 12 Prototyping and Design Tools in 2024
Invision was created in 2011 and is one of the most powerful applications you can use in 2023 for prototyping, animation, and designing. It has over 7 million global clients and boasts some awards for its cloud-based services.
Source: mockitt.wondershare.com
5 Figma Alternatives for UI & UX Designers
InVision provides an alternative solution to FigJam. As a Figma user, you’re most likely familiar with FigJam already. If not – it is an online team-based whiteboard interface where you can work together on ideas, set plans in stone, and create visual project trajectories. InVision provides the same exact solution, focusing on affordability (it has a free plan!) and...
Source: stackdiary.com
10 Best Adobe XD Alternatives (Free & Paid)
InVision is an easy-to-use tool that makes designing delightfully simple. You can smoothly create interactive and responsive prototypes. With advanced features like multi-user collaboration, vector editing, transitions & animation tools, workflow synchronization, and robust asset libraries, it is the perfect Adobe XD alternative for creating outstanding UI designs. The tool...
Source: justcreative.com

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
Source: www.assemblyai.com
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, PyTorch seems to be a lot more popular than Invision. While we know about 133 links to PyTorch, we've tracked only 4 mentions of Invision. 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.

Invision mentions (4)

  • The Best 100 Free UI/UX Resources for Every Designer & Developer
    InVision Invisionapp.com Prototyping and collaboration tool with a free plan for up to 3 projects. - Source: dev.to / 3 months ago
  • Resources for improving UI skills
    Search for UI/Design/Firma Tutorials on YouTube, check out UI related Blog posts on invisionapp.com, check out UI Inspiration muzli. Source: over 2 years ago
  • Migrating to Figma: is there a good alternative to the invisionapp.com website for design documentation and organization?
    We have 100s of different screens to migrate as well as a really large design system, and to date we've been successfully using the invisionapp.com website to keep things really well organized and easy to navigate with tags, pages, etc. We've enjoyed this system so far because it's easy for PMs and Devs to navigate in a website format, without having to learn the design software or get bogged down in artboards. Source: almost 3 years ago
  • Best platform for online tutoring?
    Other options: explain everything whiteboard, invisionapp.com. Source: over 3 years ago

PyTorch mentions (133)

  • Grasping Computer Vision Fundamentals Using Python
    To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 28 days ago
  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / about 1 month ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / 2 months ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 4 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 4 months ago
View more

What are some alternatives?

When comparing Invision and PyTorch, you can also consider the following products

Figma - Team-based interface design, Figma lets you collaborate on designs in real time.

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.

Adobe XD - Adobe XD is an all-in-one UX/UI solution for designing websites, mobile apps and more. 

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

Marvel - Turn sketches, mockups and designs into web, iPhone, iOS, Android and Apple Watch app prototypes.

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

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