Based on our record, AlternativeTo seems to be a lot more popular than Scikit-learn. While we know about 424 links to AlternativeTo, we've tracked only 29 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.
Alternativeto - References all types of software on all OS : Windows, Mac, Linux, Android, etc. - Source: dev.to / about 1 month ago
This is the best that I've ever used to search for similar software: https://alternativeto.net/ No alternative to it that I'm aware of. - Source: Hacker News / 3 months ago
Https://alternativeto.net/ fills that role for me, it has crowd-sourced reviews, searchable facets, and of course recommendations. - Source: Hacker News / 3 months ago
> None of these lists ever seem to be as fleshed out, up to date, or well organized as https://github.com/awesome-selfhosted/awesome-selfhosted or "best of" lists to pick a couple options to evaluate in more depth. If I analyzed 10 times as many options I might discover really wonderful projects I would have otherwise missed, but I struggle to imagine having that kind of time. - Source: Hacker News / 3 months ago
There are plenty of video editors available. Go to alternativeto.net which allows you to search for, well, alternatives to your existing apps. Source: 7 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 / 22 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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