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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.
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 / 2 months 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 / 4 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 / 6 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 / 7 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 / 8 months ago
How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 19 days ago
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 / 4 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 / about 1 year 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: about 1 year 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
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