Causal App
Pry Financials
Finmark
Sturppy
Forecastr
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Based on our record, OpenCV should be more popular than Causal App. It has been mentiond 52 times since March 2021. 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.
IMO the better paradigm is coming from enterprise applications like Anaplan. Cells are not the right abstraction to work with numbers. Most of the time you work with multi-dimensional quantities (eg revenue by product, geography, month). We’re working on a more approachable implementation of that paradigm at https://causal.app. - Source: Hacker News / 21 days ago
We're using Hypertune at https://causal.app for a few months now and it's been great! We have a few feature flags in there but also some more complex typed data for our onboarding modals. - Source: Hacker News / about 1 year ago
Congrats on the launch! We've been using Hypertune at Causal (https://causal.app) for the last few months and it's saved tonnes of engineering cycles letting me and our PM iterate directly on custom onboarding copy for different Causal templates, alongside more typical feature flag use-cases :). - Source: Hacker News / about 1 year ago
If you're particularly keen go onto some of the prep courses there are out there. wall street prep is one, there are other PE prep courses hawked on here for as little as 10 bucks. All are built around excel skills and learning DCFs. I recommend causal.app if you want to try to skip some of this and get forced into a tool. Source: about 1 year ago
Hi HN, I'm the founder of https://causal.app and the author of this post — Most of the finance content online is very textbook-y and overkill for early stage cos, so wanted this to be a 'no-nonsense' guide for founders/ops people that have to juggle a bit of finance stuff alongside everything else. We've helped lots of startups across different stages with finance stuff over the last few years through Causal, so... - Source: Hacker News / over 1 year 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 / 19 days ago
Open the camera feed — and use the OpenCV library for real-time computer vision processing. - Source: dev.to / about 1 month ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 7 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 7 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 11 months ago
Pry Financials - Finance for Founders
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Finmark - Financial planning software for startups
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Sturppy - Helping founders around the world create investor-ready financial models & forecasts
NumPy - NumPy is the fundamental package for scientific computing with Python
