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Based on our record, Nim (programming language) should be more popular than Scikit-learn. It has been mentiond 142 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.
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
I'd be interested to hear the author's take on Nim [1], which seems to be better suited for game development than Rust by staying out of the dev's way [2], and supports hot-reloading (at least in Unreal Engine 5) [3]? [1] https://nim-lang.org/ [2] https://youtu.be/d2VRuZo2pdA?si=E3N62oUJ-clXozCg [3] https://www.youtube.com/watch?v=Cdr4-cOsAWA. - Source: Hacker News / 20 days ago
I think the right answer to your question would be NimLang[0]. In reality, if you're seeking to use this in any enterprise context, you'd most likely want to select the subset of C++ that makes sense for you or just use C#. [0]https://nim-lang.org/. - Source: Hacker News / 3 months ago
I don't think it's a rust-inspired language, but since it has strong typing and compiles to javascript, did you give a look at nim [0] ? For what it takes, I find the language very expressive without the verbosity in rust that reminds me java. And it is also very flexible. [0] : https://nim-lang.org/. - Source: Hacker News / 5 months ago
FYI, on the front page, https://nim-lang.org, in large type you have this: > Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. - Source: Hacker News / 5 months ago
You better off with using a compiled language. If you interested in a language that's compiled, fast, but as easy and pleasant as Python - I'd recommend you take a look at [Nim](https://nim-lang.org). And to prove what Nim's capable of - here's a cool repo with 100+ cli apps someone wrote in Nim: [c-blake/bu](https://github.com/c-blake/bu). - Source: Hacker News / 7 months ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Crystal (programming language) - Programming language with Ruby-like syntax that compiles to efficient native code.
OpenCV - OpenCV is the world's biggest computer vision library
D (Programming Language) - D is a language with C-like syntax and static typing.
NumPy - NumPy is the fundamental package for scientific computing with Python
Zig - Zig is a general-purpose programming language designed for robustness, optimality, and maintainability.