Introducing ML News

Written by rachelrapp | Published 2020/11/16
Tech Story Tags: machine-learning | artificial-intelligence | community-building | data-science | deep-learning | ai | ml | machine-learning-news

TLDR ML News is a community for sharing and discussing all things related to machine learning, deep learning, AI, data science, and the like. The site mainly consists of two pages: “top,” and “new” The top page uses an algorithm to rank content based on a combination of upvotes and time since its submission. The algorithm aims to push the most relevant and interesting content to the front page. While the community is anonymous by nature, you’re free to add a bio so other users can learn about your background and connect with you.via the TL;DR App

I know.
There are a lot of tech/AI/[insert relevant category here] "communities" out there.
But this one is different, I promise.
ML News (MLN for short) is a community for sharing and discussing all things related to machine learning, deep learning, AI, data science, and the like.
It all started with a love-hate relationship with Hacker News. On a good day you might find a gem or two. However, in my experience you're more likely to waste five minutes scanning a bunch of random links to people's personal blogs, and pop news articles talking about something [insert some big company] did.
Enter: the other communities. There's Lobste.rs, r/MachineLearning, the original Slashdot—you name it. While r/MachineLearning has its merits, it's extremely limited. I mean "non-arxiv link posts only allowed on weekends", limited. Meanwhile the other channels, in my experience, are often flooded with not-so-relevant posts which somehow fall under the "tech" umbrella. Sometimes they're not relevant at all.
That's why we decided to create a dedicated place for experts and enthusiasts to share content related to machine learning. We hope that by narrowing the scope, we can build a space where ML people like ourselves can easily find interesting news, breakthroughs, and updates in the field, or essentially anything which could pique our interest. From ML experts to AI enthusiasts, this is a community that values honest debate, curiosity, positivity, and good humor. We'd love to hear your voice as well.

How It Works

If you’ve used Hacker News before, MLN will look familiar. 
The site mainly consists of two pages: “top,” and “new”. The new page lists posts in chronological order. The top page uses an algorithm to rank content based on a combination of upvotes and time since its submission. The algorithm aims to push the most relevant and interesting content to the front page.
In addition to helping earn your posts a higher rank on the top page, upvotes award the poster with karma. You can also comment on posts, and discuss or debate different topics with the community (one of my favorite parts of the site, personally).
From your profile (or by clicking on another user’s profile) you can see post and comment history, a user’s karma, and how long they’ve been a member of MLN. While the community is anonymous by nature, you’re free to add a bio so other users can learn about your background and/or connect with you. It’s a great way to network with other members, make yourself known, and add credibility to your posts.
Based on some early feedback, we just added RSS feed support so you can consume the top content in whatever RSS reader you prefer.
Last but not least, please also let us know what you think. If you have any comments, suggestions, or feedback, reach out!
And most importantly, welcome to ML News.

Written by rachelrapp | Interested in signal processing, ML, and writing.
Published by HackerNoon on 2020/11/16