At some point during your machine learning journey you may get stuck on a problem, start to lose motivation, or find yourself unable to keep up the rapid rate of new developments. In these situations, I find communities have a lot to offer regardless of your skill level.

There are tons of communities out there — however, many are no longer active or not well-moderated. To help streamline your search, I’ve curated a list of (what I think) are some of the most active, helpful, and interesting communities to check out — not just based on overall size. I’ve also included a couple of niche communities if you’re interested in discovering new topics to explore.

1. For general discussion and latest news: r/machinelearning

Reddit is home to a whole host of forums (known as subreddits) covering various aspects of machine learning. Of these, r/machinelearning is the go-to subreddit with over 2 million members sharing machine learning projects, latest research, and discussions. It’s well-moderated and regularly contributed to by industry veterans, meaning you’ll find plenty of quality content here.

If you’re looking for something a bit more beginner-friendly, I’d recommend checking out r/learnmachinelearning instead. This is where you can ask beginner questions and share beginner projects for feedback (they also have a Discord server).

Some other related subreddits you might find useful include:

• r/datascience (500K+ members) — discussion on data science careers
• r/artificial (145K+ members) — general AI news
• r/reinforcementlearning (20K+ members) — focused on reinforcement learning

2. For competitions: Kaggle

Kaggle is the biggest data science competition platform. They partner with businesses to run challenges made up of a dataset and problem statement for anyone in the world to solve. Challenge topics vary from computer vision to stock exchange predictions. Joining a competition and contributing to the Kaggle Forums can be a useful way to collaborate with others working on the same project as you. Here you’ll be able to discuss approaches, algorithms, and advice for feature engineering.

If the current competitions on Kaggle aren’t to your liking, some other data science competition platforms worth checking out include AICrowd, Omdena, MachineHack, DrivenData, and Zindi.

3. For getting started: Learn AI Together Discord

Learn AI together has over 24,000 members and is one of the largest AI communities on Discord. The community is managed by Louis at What’s AI — a YouTube channel dedicated to beginner-friendly resources on getting started in machine learning. There’s a huge list of discussion topics from AGI to Kaggle competitions to healthcare (30+ and counting!), and dedicated sections to ask questions and share resources on the latest news and events.

4. For NLP: Hugging Face

Hugging Face started originally with open-source tools for NLP projects, but has since expanded into fields such as Computer Vision and Reinforcement Learning. On the Hugging Face platform you can download and share models, and discuss projects on their Discord or Forum. If you’re having trouble figuring what type of project to build, heading over to Hugging Face may be a great source of inspiration.

5. For reinforcement learning: Reinforcement Learning Discussion Discord

Reinforcement Learning Discussion is an active Discord server with over 3,000 members. It’s managed by researchers in the reinforcement learning field, and they’re particularly friendly and catering for beginners. It can be a great place to ask questions on popular courses such as DeepMind’s Reinforcement Learning lectures or Spinning Up by OpenAI, share progress and experiments with public reinforcement learning environments, and stay up-to-date on the latest research (many authors will share their latest papers directly in the server).

6. For DALL-E and similar generative projects: LAION

LAION is a not-for-profit community whose main goal is to work together to replicate OpenAI’s DALL-E. They have an active Discord server with over 3,000 members at the time of writing. It’s a great place to keep up with (and contribute to) the open-source project, discuss related audio/video/3D topics, and share your own generative project for feedback.

7. For AI in gaming: StartCraft II AI Arena

If the achievements of Deepmind’s AlphaStar or OpenAI’s Dota 2 AI brought you into the space, you might be interested in checking out AI Arena. They’re a community of researchers, practitioners, and hobbyists building both scripted and deep learning agents for StarCraft II. They have an open Discord for meeting others, run regular community streams on Twitch, and provide getting started resources for creating your own agent to enter their ranked tournament ladders.

Closing Remarks

I hope that this list has helped you find a new community to meet others on a similar journey and take your skills to the next level. Join one or try them all to see what suits you best. Good luck!