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Based on our record, NumPy should be more popular than Causal App. It has been mentiond 112 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.
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
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 / 24 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
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Pry Financials - Finance for Founders
OpenCV - OpenCV is the world's biggest computer vision library
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