Based on our record, Mastodon seems to be a lot more popular than Scikit-learn. While we know about 613 links to Mastodon, we've tracked only 28 mentions of Scikit-learn. 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.
Did you miss the part where Chris Espinosa said "That’s not Sherry Livingston"? Chris also has a follow-up post not shown in Cabel's blog where he says there aren't any photos of Sherry online: https://mastodon.social/@Cdespinosa/112391173495267599. - Source: Hacker News / 4 days ago
Personally, I really like this summary: https://mastodon.social/@nixCraft/112444973228241564. - Source: Hacker News / 5 days ago
Just a follow up to all downvoters: developers care, and are working on improving performance, take a look at one of hopefully many to come, examples - https://mastodon.social/@tdp_org/112440017216320486. - Source: Hacker News / 9 days ago
Here's a cached copy of the linked post on a server with more capacity: https://mastodon.social/@ben@m.benui.ca/112396505994216742. - Source: Hacker News / 13 days ago
Today’s Xcode 15.4 RC suggests that “Donan” is the M4 core codename, and that it may support ARM’s SME instructions. https://mastodon.social/@bshanks/112401605018159567. - Source: Hacker News / 14 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 / 3 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: 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
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
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Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
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OpenCV - OpenCV is the world's biggest computer vision library
Diaspora - The online social world where you are in control.
NumPy - NumPy is the fundamental package for scientific computing with Python