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Logistic regression is a machine learning classification algorithm that is used to predict the probability of certain classes based on some dependent variables
Learn about some of the most well known machine learning algorithms in less than a minute each.
How does Refind curate?
It’s a mix of human and algorithmic curation, following a number of steps:
- We monitor 10k+ sources and 1k+ thought leaders on hundreds of topics—publications, blogs, news sites, newsletters, Substack, Medium, Twitter, etc.
- In addition, our users save links from around the web using our Save buttons and our extensions.
- Our algorithm processes 100k+ new links every day and uses external signals to find the most relevant ones, focusing on timeless pieces.
- Our community of active users gets the most relevant links every day, tailored to their interests. They provide feedback via implicit and explicit signals: open, read, listen, share, mark as read, read later, «More/less like this», etc.
- Our algorithm uses these internal signals to refine the selection.
- In addition, we have expert curators who manually curate niche topics.
The result: lists of the best and most useful articles on hundreds of topics.
How does Refind detect «timeless» pieces?
We focus on pieces with long shelf-lives—not news. We determine «timelessness» via a number of metrics, for example, the consumption pattern of links over time.
How many sources does Refind monitor?
We monitor 10k+ content sources on hundreds of topics—publications, blogs, news sites, newsletters, Substack, Medium, Twitter, etc.
Can I submit a link?
Indirectly, by using Refind and saving links from outside (e.g., via our extensions).
How can I report a problem?
When you’re logged-in, you can flag any link via the «More» (...) menu. You can also report problems via email to email@example.com
Who uses Refind?
250k+ smart people start their day with Refind. To learn something new. To get inspired. To move forward. Our apps have a 4.9/5 rating.
Is Refind free?
Yes, it’s free!
How can I sign up?
Head over to our homepage and sign up by email or with your Twitter or Google account.