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Nim (programming language) VS Scikit-learn

Compare Nim (programming language) VS Scikit-learn and see what are their differences

Nim (programming language) logo Nim (programming language)

The Nim programming language is a concise, fast programming language that compiles to C, C++ and JavaScript.

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Nim (programming language) Landing page
    Landing page //
    2021-07-31
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Nim (programming language) videos

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Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

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  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

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Data Science And Machine Learning
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Reviews

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Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Social recommendations and mentions

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.

Nim (programming language) mentions (142)

  • 3 years of fulltime Rust game development, and why we're leaving Rust behind
    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
  • "14 Years of Go" by Rob Pike
    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
  • Ask HN: Interest in a Rust-Inspired Language Compiling to JavaScript?
    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
  • Nim
    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
  • Things I've learned about building CLI tools in Python
    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
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Scikit-learn mentions (29)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    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
  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    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
  • Link Prediction With node2vec in Physics Collaboration Network
    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
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    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
  • PSA: You don't need fancy stuff to do good work.
    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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What are some alternatives?

When comparing Nim (programming language) and Scikit-learn, you can also consider the following products

Crystal (programming language) - Programming language with Ruby-like syntax that compiles to efficient native code.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

V (programming language) - Simple, fast, safe, compiled language for developing maintainable software.

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