Explore the intersection of Bayesian statistics and Deep Learning, its advantages and limitations in this easy guide
A full guide on how to prepare for a bootcamp, successfully complete the course, and act afterward
Hundreds of books are now free to download
One of the important fields of Artificial Intelligence is Computer Vision. Computer Vision is the science of computers and software systems…
You’ll need 10 minutes to implement convolutions with padding in Numpy
The next big thing, or just massively overhyped?
What’s the purpose of dashboards in 2023?
Game Theory is a method of studying strategic situations. A ‘strategic’ situation is a setting where the outcomes which affect you depend…
Common Terminology & Visual Mapping
Building Anylogic’s GIS-Feature w/ SimPy, OSMnx and Leaflet.js
Forget GIS and analyse your Polygons, LineStrings and Points with Python
The term “Neural Networks” may seem mysterious, why is an algorithm called Neural Networks? Does it really mimic real neurons, and how?
How Computers Think: Introduction
Outlining some of the most common design patterns encountered when creating successful Machine Learning solutions
A practical guide to building critical MLOps capabilities that maximize data science ROI
Make your Python code concise with these one-liners
Cleaner Code and Fewer Loops? Count me in.
Leveraging the Surprise package to build a collaborative filtering recommender in Python
Sorting items by relevance is crucial for information retrieval and recommender systems.
Kickstart your understanding of one of Tensorflow’s most powerful set of tools for deep learning
A peek into Google’s open-source strategy
Aspiring developers and data scientists too often put the cart before the horse
«Abraham Lincoln is quoted to have said, Give me six hours to chop down a tree and I will spend the first four sharpening the axe»
Causal inference, machine learning, and regularization bias
Explore best practices and enhance your prompts for better results
See BLOOM in action solving math, translation, and coding problems.
SQL tricks to make your analytics work more efficient
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 firstname.lastname@example.org
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.