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NumPy VS Invision

Compare NumPy VS Invision and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Invision logo Invision

Prototyping and collaboration for design teams
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Invision Landing page
    Landing page //
    2023-10-07

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

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.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Invision videos

+ Add

InVision Studio Review | Here's what we think!

More videos:

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

Category Popularity

0-100% (relative to NumPy and Invision)

NumPy

Invision

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

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

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

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Invision. While we know about 119 links to NumPy, 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.

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 5 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 9 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

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

What are some alternatives?

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

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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

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

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

OpenCV - OpenCV is the world's biggest computer vision library

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

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