Top Python Libraries for Data Science, Data Visualization & Machine Learning
This article compiles the 38 top Python libraries for data science, data visualization & machine learning, as best determined by KDnuggets staff.
More from KDnuggets
Free MLOps Crash Course for Beginners
Interest in, and demand for, MLOps is growing exponentially. What, exactly, is it? Why is it important? Where should you turn next to learn more? Check out this crash course to find the answers to…
How Does Logistic Regression Work?
Logistic regression is a machine learning classification algorithm that is used to predict the probability of certain classes based on some dependent variables
Machine Learning Algorithms Explained in Less Than 1 Minute Each
Learn about some of the most well known machine learning algorithms in less than a minute each.
10 Great Python Resources for Aspiring Data Scientists
By Matthew Mayo, KDnuggets. Python is one of the most widely used languages in data science, and an incredibly popular general programming language on its own. Many prospective data scientists are…
What is Refind?
Every day Refind picks the most relevant links from around the web for you. Picking only a handful of links means focusing on what’s relevant and useful. We favor timeless pieces—links with long shelf-lives, articles that are still relevant one month, one year, or even ten years from now. These lists of the best resources on any topic are the result of years of careful curation.
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 hello@refind.com
Who uses Refind?
200k+ 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.