Can I promote a paid product here?
Subreddit guides
r/MachineLearning rules, stats, and what to post
A source-backed Rankhog guide to r/MachineLearning: public rules, community context, posting fit, and startup-promotion risk before you publish.
By Anthony Riera, founder and operator of Rankhog.
Subreddit guides combine public Reddit source URLs, captured rules, visible verification dates, and Rankhog's account-safety workflow.
Current public stats
- Members
- 3,072,379
- Verified
- September 18, 2026
- Category
- AI builders, operators, and researchers
Rules can change, so Rankhog keeps verification dates and the original public Reddit sources visible.
Rule summary
- No Spam: r/MachineLearning has held a long-standing, strict policy on spam. The posts deemed to be spam will be removed, and repeat offenders will be permanently banned from participating in the subreddit.
- No Self-Promotion: r/MachineLearning does not permit the promotion of paid products, wherein the intent is clearly to promote a particular product. However, posts with links to paid products are acceptable, contingent on the fact that the post offers sufficient value to the community members and the intent is to share a resource or collect feedback for an open-dialogue. The decision will be made entirely at the discretion of the moderator team.
- No Marketing Campaigns (SEO): r/MachineLearning strictly prohibits strategic marketing campaigns targeted at community members, and posts intended to rank for SEO purposes. In the event that such behavior is caught, the user in violation of our policy will be perpetually banned with all past posts and comments purged entirely from the subreddit.
- No Disrespectful Behavior: r/MachineLearning is an all-inclusive community for a wide range of users, and thereby, kind and respectful behavior is expected in all interactions that occur on the subreddit. Therefore, please be cordial and professional at all times, and be cognizant of the fact that the user base comprises beginners interested in ML and far more experienced, technical individuals with practical experience.
- No arXiv Links without Body Text: r/MachineLearning is not a depository of bare arXiv links. Therefore, for users that share research papers, please insert some form of commentary or analysis to initiate a community-wide discussion. In other words, low-effort posts will be removed for research papers.
- No Low-Effort, Beginner Questions: r/MachineLearning will expand its scope to allow more content oriented around beginners, for a broader audience to participate in the subreddit. However, there is a fine-line between a question posted by user who, evidently, put in the time to research ML concepts and effort to communicate the guidance needed from industry practitioners, and then those that post questions that can be easily found online. The latter type of post will be removed from the subreddit.
Works well
- Share a research paper with a paragraph of your own analysis and a question to start discussion.
- Post a technical writeup or project breakdown that offers value to practitioners, with a link to a paid product only if you are seeking open feedback.
- Ask a well-researched question that shows you already tried to find the answer and explains what guidance you need from experienced practitioners.
Avoid
- Do not drop a bare arXiv link without adding your own commentary or analysis, as it will be removed under the
- No arXiv Links without Body Text
- rule.
- Do not post beginner questions that can be easily answered with a quick online search, or you will trip the
- No Low-Effort, Beginner Questions
- rule and see your post removed.
What r/MachineLearning Is For
This community is for machine learning discussion and research sharing. The public description tells beginners to go elsewhere, directs AGI talk to another subreddit, sends career advice to a different community, and points dataset seekers to a datasets subreddit. The rules say the room is meant for a wide range of users, from beginners interested in ML to far more experienced technical individuals with practical experience.
Rules That Matter Before Posting
The rules that decide whether your post survives are
What To Post
A good post here is one that gives the community something to talk about. If you are sharing a research paper, add your own commentary or analysis so people have a reason to discuss it. If you are a founder with a paid product, only post if you are offering real value and genuinely looking for feedback, not just trying to sell. Show that you understand the room and respect the people in it.
What To Avoid
Your post gets removed or you get banned if you spam, run a marketing campaign, or post for SEO purposes. The
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Common questions about r/MachineLearning
Can I share an arXiv paper?
Is this the right place for beginner questions?
Is this the right place for beginner questions?
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