About Data & Machine Learning
An international community of people interested in data & machine learning.
The community at a glance
Data & Machine Learning is a X / Twitter Community for Data Scientists and ML Engineers with roughly 61 members. It uses a forum format for communication.
Community Topics
Community Features
This community has a forum
Frequently asked questions
- Who is Data & Machine Learning for?
- Best for Data Scientists and ML Engineers enthusiasts looking for a X / Twitter-based community with forum discussion.
- Is Data & Machine Learning free to join?
- This listing is not marked as paid-only. Access rules and any fees are decided by the community.
- How many members does Data & Machine Learning have?
- Roughly 61 members, based on figures reported by the community or its host. Member counts are approximate and change over time.
- What platform is Data & Machine Learning on?
- Data & Machine Learning runs on X / Twitter. Twitter (recently renamed to X) is an American microblogging and social networking service on which users post and interact with messages known as "tweets". Registered users can post, like and retweet tweets, but unregistered users can only read them. Twitter had a community feature where user's tweets in a group are aggregated in one place, and are read-only to people outside of the community. However, they are discontinuing the communities feature as it was not used enough :(
- What topics does Data & Machine Learning cover?
- On the Hive Index, Data & Machine Learning is organized under Data Scientists, ML Engineers.
- How do I join Data & Machine Learning?
- You can join Data & Machine Learning by clicking this link, or pressing the "Go to community" button above.
- What are the Data Science communities like?
- Communities for data scientists and analysts covering machine learning, statistics, Python, and real-world data projects. Slack, Discord, and Reddit all have active communities, ranging from beginner-friendly spaces for breaking into the field to more technical groups discussing research papers and production ML systems.
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