Leanbe.ai
productboard
Roadmap
Canny
Poda
Waymark
AnnounceKit
ProductFlare
Pandas
NumPy
OpenCV
Scikit-learn
Dataiku
Exploratory
htm.java
WEKA
Have you ever built a product feature that simply didn't meet your users' expectations or real needs? We have, too. That's why we created Leanbe. It is a smart tool covering all the 3 steps in the product development cycle: feedback collection, roadmap generation and user notification. Thus the full loop of data collection, analysis and planning the future actions is based on a data-driven and user-oriented approach. Leanbe is a platform that helps collect feedback & feature requests, generate a roadmap & notify users about releases and updates.
Leanbe.ai PandasNo features have been listed yet.
Based on our record, Pandas seems to be a lot more popular than Leanbe.ai. While we know about 201 links to Pandas, we've tracked only 7 mentions of Leanbe.ai. 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.
A lot of times here in this subreddit we talked about Beupify and finally me, with the team worked on your feedback and we would have absolutely different and new website just in 2 weeks. I am here to ask you again for feedback as there is left not that much time so we can implement other suggestions as well. For the ones who are not familiar with the tool, I would love to mention that it was only a tool to... Source: about 3 years ago
If it's not against the tools of the subreddit - you can check the website and give me some advice if possible. Source: about 3 years ago
Guys, you were writing me about the startup - here is it https://beupify.com/. Source: about 3 years ago
You can check out the tool, and ping me if you have any questions! Source: about 3 years ago
Here are some tips that helped us to scale our business. P.S The tool is Beupify which is an all-in-one solution for the release notes :). Source: over 3 years ago
How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 17 days ago
Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation. - Source: dev.to / 23 days ago
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / about 2 months ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 2 months ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 2 months ago
productboard - Beautiful and powerful product management.
NumPy - NumPy is the fundamental package for scientific computing with Python
Roadmap - Collision avoidance for projects and people
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.
