NimbleText
WordCounter.net
Text Workflow
TextPipe
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ThinkCalculator
Manipulist
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NumPy
Pandas
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htm.java
Figure Eight
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Based on our record, NumPy seems to be a lot more popular than NimbleText. While we know about 122 links to NumPy, we've tracked only 12 mentions of NimbleText. 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.
It's not a game-changer for me. I like to have it, but I'm also still using tools like NimbleText and thinking about source generators for a lot of stuff. Source: about 3 years ago
Writing a program to generate some tedious C# is actually a fine endeavor. I've done it plenty of times! You should also have a look at NimbleText. Then you don't even have to write 80% of the script! Source: about 3 years ago
That gets really, really old really, really fast. Every control you write probably has 2-5 of these, and in extreme cases a control might have more than a dozen. I already use the templating tool NimbleText to help with this. It'd be a lot nicer if I could just write a prompt like:. Source: over 3 years ago
That said, if you don't feel like waiting around to see if I actually do the example (I don't always keep these promises), for stuff like this there's a tool called NimbleText I've been using to generate the class for me. There's a free online version that will do the trick and it doesn't take too long to figure out. The main "downside" compared to source generation is you have to copy/paste it yourself. Source: over 3 years ago
NimbleText lets me write a template for one instance of that code, then I can fill in data lines and let it generate the rest. It's kind of like a source generator, only at write-time, not compile-time. It's done more work to make dependency properties palatable than Microsoft ever has. Source: over 3 years ago
Unmatched integration with ML/AI ecosystems through NumPy, TensorFlow, and PyTorch. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
AI starts with math and coding. You donโt need a PhDโjust high school math like algebra and some geometry. Linear algebra (think matrices) and calculus (like slopes) help understand how AI models work. Python is the main language for AI, thanks to tools like TensorFlow and NumPy. If you know JavaScript from Vue.js, Pythonโs syntax is straightforward. - Source: dev.to / 12 months ago
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / over 1 year ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / almost 2 years ago
WordCounter.net - Count words, sentences, paragraphs etc.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Text Workflow - Text Workflow app for Mac
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
TextPipe - Search and Replace, Find and Replace, Web Sites, Database Extracts, XML, CSV, Tab, mainframe COBOL data and more
OpenCV - OpenCV is the world's biggest computer vision library