productboard
Aha
Canny
ProdPad
Upvoty
Jira
Asana
UserVoice
NumPy
Pandas
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
productboardBased 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.
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
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
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
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
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
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
NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 27 days ago
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
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
Aha - Aha! is the new way to create visual product roadmaps. Web-based product management tools and roadmapping software for agile product managers.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Canny - Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.
OpenCV - OpenCV is the world's biggest computer vision library
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.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
