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NumPy VS productboard

Compare NumPy VS productboard and see what are their differences

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

productboard logo productboard

Beautiful and powerful product management.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • productboard Landing page
    Landing page //
    2023-05-05

NumPy videos

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

productboard videos

ProductBoard Review | Project Management Tool | Pearl Lemon Review

More videos:

  • Review - Welcome to productboard!
  • Review - ProductBoard Helps You Make the Right Thing at Disrupt SF Startup Battlefield

Category Popularity

0-100% (relative to NumPy and productboard)
Data Science And Machine Learning
Project Management
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Customer Feedback
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 NumPy and productboard

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.
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

productboard Reviews

We have no reviews of productboard yet.
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Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than productboard. While we know about 112 links to NumPy, we've tracked only 4 mentions of productboard. 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 (112)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include... - Source: dev.to / 22 days ago
  • Documenting my pin collection with Segment Anything: Part 3
    NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations. - Source: dev.to / 22 days ago
  • Awesome List
    NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 27 days ago
  • NumPy for Beginners: A Basic Guide to Get You Started
    This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples. - Source: dev.to / 29 days ago
  • 2 Minutes to JupyterLab Notebook on Docker Desktop
    Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 10 months ago
View more

productboard mentions (4)

  • Do you use an additional tool aside from JIRA?
    Admittedly, this is an issue with organization and can be solved with thorough cleanups, but I suspect that may disrupt the usual flow of non-PM people more. I am thinking of using a separate tool like craft.io or productboard.com to highlight strategies, roadmaps, cross-team initiatives, discoveries, etc. With a possible link to JIRA somehow. Has anyone ever tried this? Source: about 2 years ago
  • Think twice before using AGE in PotgreSQL
    Recently my friend at Productboard noticed an interesting bug in one of our services. For some reason our code responsible for calculating how many days our customers' features spend in certain states (Idea, Discovery, Delivery, etc) in some cases would give us wrong results. - Source: dev.to / about 2 years ago
  • Which tools you use in your role of PM?
    ProductboardProductboard helps us capture user feedback from email, Slack, Zendesk, our public-facing product portal etc. And see what users need the most. We also use it for prioritizing product objectives, release planning, roadmapping…. Source: almost 3 years ago
  • Ask HN: What software do you use to gather requirements?
    I use ProductBoard. It's fairly expensive but pretty great. I gather requirements into PB and use the inbuilt editor to flesh them out. When a story is ready I push a button and it ends up in Trello (but you can add your own integrations; there's one for github for example). The integrations aren't perfect but I love it. Used it in my last job and brought it in at my current job. https://productboard.com. - Source: Hacker News / about 3 years ago

What are some alternatives?

When comparing NumPy and productboard, 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.

Aha - Aha! is the new way to create visual product roadmaps. Web-based product management tools and roadmapping software for agile product managers.

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

Canny - Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.

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

ProdPad - ProdPad helps your team gather ideas, surface the best ones and turn them into product specs, and then put it all on a product roadmap.