Communities

Writing
Writing
Codidact Meta
Codidact Meta
The Great Outdoors
The Great Outdoors
Photography & Video
Photography & Video
Scientific Speculation
Scientific Speculation
Cooking
Cooking
Electrical Engineering
Electrical Engineering
Judaism
Judaism
Languages & Linguistics
Languages & Linguistics
Software Development
Software Development
Mathematics
Mathematics
Christianity
Christianity
Code Golf
Code Golf
Music
Music
Physics
Physics
Linux Systems
Linux Systems
Power Users
Power Users
Tabletop RPGs
Tabletop RPGs
Community Proposals
Community Proposals
tag:snake search within a tag
answers:0 unanswered questions
user:xxxx search by author id
score:0.5 posts with 0.5+ score
"snake oil" exact phrase
votes:4 posts with 4+ votes
created:<1w created < 1 week ago
post_type:xxxx type of post
Search help
Notifications
Mark all as read See all your notifications »
Users Search
Help Dashboard Sign In Sign Up
Descriptions Incubator Q&A Meta
Descriptions
Posts Tags Edits
Start Proposal

Welcome to the staging ground for new communities! Each proposal has a description in the "Descriptions" category and a body of questions and answers in "Incubator Q&A". You can ask questions (and get answers, we hope!) right away, and start new proposals.

Are you here to participate in a specific proposal? Click on the proposal tag (with the dark outline) to see only posts about that proposal and not all of the others that are in progress. Tags are at the bottom of each post.

Post History

Descriptions Machine Learning

The Machine Learning (ML) community aims to provide a platform for anyone interested in helping computers learn from data. We mainly target people with backgrounds in data science, machine learnin...

posted 1y ago by mr Tsjolder‭  ·  edited 1y ago by mr Tsjolder‭

Wiki machine-learning
#3: Post edited by user avatar mr Tsjolder‭ · 2023-10-14T14:49:32Z (about 1 year ago)
add section on minimum effort requirement
  • The **Machine Learning** (ML) community aims to provide a platform for anyone interested in helping computers learn from data.
  • We mainly target people with backgrounds in data science, machine learning and data visualisation, but also statisticians, computer scientists and anyone looking to learn about the technical side of ML are more than welcome.
  • ### Topics
  • The goal would be to have a platform for technical (focus on math and/or implementation) questions about:
  • - supervised learning
  • - unsupervised/self-supervised learning
  • - deep learning and neural networks
  • - reinforcement learning
  • - data collection and pre-processing
  • - data visualisation
  • - data-driven computing
  • - applied statistics
  • - statistical learning theory
  • - predictive modelling
  • - Bayesian modelling
  • - applying ML models to data
  • - deployment of ML pipelines
  • - computational neuroscience
  • - prompt engineering
  • - ...
  • ### Off-Topic
  • To keep the community focused on ML, questions about the following topics should be asked elsewhere:
  • - pure coding questions (should be asked on software.codidact.com).
  • E.g. _How can I visualise this data with `matplotlib`?_ would be on-topic, but _How can I change the background colour of plots in `matplotlib`?_ should **not** be a question for this community.
  • - pure math and statistics questions (should be asked on math.codidact.com).
  • E.g. _What integrals do I need to compute the expectation of this random variable?_ would be okay, but _How do I compute this complex integral?_ would **not** be okay.
  • - system administration questions (should probably be asked on powerusers.codidact.com or linux.codidact.com).
  • E.g. _Are there any libraries that I can use to deploy my model using docker?_ is allowed, but _How do I set up docker?_ would **not** be suited.
  • - questions about other parts of Artificial Intelligence (AI) that have nothing to do with ML or ML algorithms. For these questions, a computer science community (cf. https://cs.stackexchange.com/) might be better suited.
  • E.g. _How does the AlphaZero chess engine learn to play chess?_ would be okay because AlphaZero involves learning, but _How can I build a chess engine using [alpha-beta pruning](https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning)?_ does not involve any ML and is therefore **not** suited for this community.
  • - requests for prompts or improvements to prompts for generating data (this requires a different kind of knowledge and is often considered to be the alchemy branch of ML).
  • E.g. _How does chain-of-thought prompting help the model to improve predictions?_ is a valid question, but _How can I fix this prompt for generating images with better lightning?_ is **not** okay.
  • - bug reports or other complaints about software (look for a bug tracker instead).
  • - questions about non-technical aspects of ML (e.g. opinions, ethics, legal, etc.).
  • - anything that is not (indirectly) related to machine learning.
  • ### Community Situation
  • Overlap on codidact will probably be mostly [software](https://software.codidact.com), [math](https://math.codidact.com) and [powerusers](https://powerusers.codidact.com)/[linux](https://linux.codidact.com) (as indicated above).
  • Maybe the [AI Tech proposal](https://proposals.codidact.com/posts/289124) could also be incorporated into this community (also, see below).
  • Currently, the community is shattered over [Cross Validated](https://stats.stackexchange.com) and [Data Science](https://datascience.stackexchange.com). There is also a [sub-reddit](https://www.reddit.com/r/MachineLearning/) that is (at the time of writing) protesting against what Reddit is doing.
  • ### Additional Features
  • This community will definitely need support for **MathJax** and **code blocks**, but not sure if these are really additional.
  • Given that machine learning is becoming more and more well-known in non-technical contexts, it might be useful to set up a separate discussion zone where non-technical discussions, prompt engineering, ethics, etc. could get a place in the community.
  • This might make it possible to incorporate the [AI Tech proposal](https://proposals.codidact.com/posts/289124).
  • However, I didn't completely think this through yet.
  • I welcome any sort of feedback and/or suggestions for improvement!
  • PS: I would greatly appreciate it if someone would have time/be interested to ask some questions on ML.
  • I tend to find it easier to answer questions than to ask them.
  • The **Machine Learning** (ML) community aims to provide a platform for anyone interested in helping computers learn from data.
  • We mainly target people with backgrounds in data science, machine learning and data visualisation, but also statisticians, computer scientists and anyone looking to learn about the technical side of ML are more than welcome.
  • ### Topics
  • The goal would be to have a platform for technical (focus on math and/or implementation) questions about:
  • - supervised learning
  • - unsupervised/self-supervised learning
  • - deep learning and neural networks
  • - reinforcement learning
  • - data collection and pre-processing
  • - data visualisation
  • - data-driven computing
  • - applied statistics
  • - statistical learning theory
  • - predictive modelling
  • - Bayesian modelling
  • - applying ML models to data
  • - deployment of ML pipelines
  • - computational neuroscience
  • - prompt engineering
  • - ...
  • Before asking a question, users are expected to have invested at least some effort to find an answer by themselves (cf. [this meta discussion](https://meta.codidact.com/posts/289951)).
  • Questions with readily available answers on e.g. Wikipedia will probably be closed.
  • If this search was unsuccessful or the found answer was incomprehensible or has dubious origins, we will be happy to answer the question.
  • However, the question should clarify why the search results do not answer the question.
  • Answered questions from the StackExchange network can be asked again here, as long as licences are respected (do not copy questions you do not own).
  • ### Off-Topic
  • To keep the community focused on ML, questions about the following topics should be asked elsewhere:
  • - pure coding questions (should be asked on software.codidact.com).
  • E.g. _How can I visualise this data with `matplotlib`?_ would be on-topic, but _How can I change the background colour of plots in `matplotlib`?_ should **not** be a question for this community.
  • - pure math and statistics questions (should be asked on math.codidact.com).
  • E.g. _What integrals do I need to compute the expectation of this random variable?_ would be okay, but _How do I compute this complex integral?_ would **not** be okay.
  • - system administration questions (should probably be asked on powerusers.codidact.com or linux.codidact.com).
  • E.g. _Are there any libraries that I can use to deploy my model using docker?_ is allowed, but _How do I set up docker?_ would **not** be suited.
  • - questions about other parts of Artificial Intelligence (AI) that have nothing to do with ML or ML algorithms. For these questions, a computer science community (cf. https://cs.stackexchange.com/) might be better suited.
  • E.g. _How does the AlphaZero chess engine learn to play chess?_ would be okay because AlphaZero involves learning, but _How can I build a chess engine using [alpha-beta pruning](https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning)?_ does not involve any ML and is therefore **not** suited for this community.
  • - requests for prompts or improvements to prompts for generating data (this requires a different kind of knowledge and is often considered to be the alchemy branch of ML).
  • E.g. _How does chain-of-thought prompting help the model to improve predictions?_ is a valid question, but _How can I fix this prompt for generating images with better lightning?_ is **not** okay.
  • - bug reports or other complaints about software (look for a bug tracker instead).
  • - questions about non-technical aspects of ML (e.g. opinions, ethics, legal, etc.).
  • - anything that is not (indirectly) related to machine learning.
  • ### Community Situation
  • Overlap on codidact will probably be mostly [software](https://software.codidact.com), [math](https://math.codidact.com) and [powerusers](https://powerusers.codidact.com)/[linux](https://linux.codidact.com) (as indicated above).
  • Maybe the [AI Tech proposal](https://proposals.codidact.com/posts/289124) could also be incorporated into this community (also, see below).
  • Currently, the community is shattered over [Cross Validated](https://stats.stackexchange.com) and [Data Science](https://datascience.stackexchange.com). There is also a [sub-reddit](https://www.reddit.com/r/MachineLearning/) that is (at the time of writing) protesting against what Reddit is doing.
  • ### Additional Features
  • This community will definitely need support for **MathJax** and **code blocks**, but not sure if these are really additional.
  • Given that machine learning is becoming more and more well-known in non-technical contexts, it might be useful to set up a separate discussion zone where non-technical discussions, prompt engineering, ethics, etc. could get a place in the community.
  • This might make it possible to incorporate the [AI Tech proposal](https://proposals.codidact.com/posts/289124).
  • However, I didn't completely think this through yet.
  • I welcome any sort of feedback and/or suggestions for improvement!
  • PS: I would greatly appreciate it if someone would have time/be interested to ask some questions on ML.
  • I tend to find it easier to answer questions than to ask them.
#2: Post edited by user avatar mr Tsjolder‭ · 2023-08-19T15:45:31Z (over 1 year ago)
include prompt engineering, exclude "classical" AI
  • The **Machine Learning** (ML) community aims to provide a platform for anyone interested in helping computers learn from data.
  • We mainly target people with backgrounds in data science, machine learning and data visualisation, but also statisticians, computer scientists and anyone looking to learn about the technical side of ML are more than welcome.
  • ### Topics
  • The goal would be to have a platform for technical (focus on math and/or implementation) questions about:
  • - supervised learning
  • - unsupervised/self-supervised learning
  • - deep learning and neural networks
  • - reinforcement learning
  • - data collection and pre-processing
  • - data visualisation
  • - data-driven computing
  • - applied statistics
  • - statistical learning theory
  • - predictive modelling
  • - Bayesian modelling
  • - applying ML models to data
  • - deployment of ML pipelines
  • - computational neuroscience
  • - ...
  • ### Off-Topic
  • To keep the community focused on ML, questions about the following topics should be asked elsewhere:
  • - pure coding questions (should be asked on software.codidact.com).
  • E.g. _How can I visualise this data with `matplotlib`?_ would be on-topic, but _How can I change the background colour of plots in `matplotlib`?_ should **not** be a question for this community.
  • - pure math and statistics questions (should be asked on math.codidact.com).
  • E.g. _What integrals do I need to compute the expectation of this random variable?_ would be okay, but _How do I compute this complex integral?_ would **not** be okay.
  • - system administration questions (should probably be asked on powerusers.codidact.com or linux.codidact.com).
  • E.g. _Are there any libraries that I can use to deploy my model using docker?_ is allowed, but _How do I set up docker?_ would **not** be suited.
  • - bug reports or other complaints about software (look for a bug tracker instead)
  • - questions about prompt engineering (because I believe the majority of technical people would consider this alchemy).
  • - questions about non-technical aspects of ML (e.g. opinions, ethics, legal, etc.).
  • - anything that is not (indirectly) related to machine learning.
  • ### Community Situation
  • Overlap on codidact will probably be mostly [software](https://software.codidact.com), [math](https://math.codidact.com) and [powerusers](https://powerusers.codidact.com)/[linux](https://linux.codidact.com) (as indicated above).
  • Maybe the [AI Tech proposal](https://proposals.codidact.com/posts/289124) could also be incorporated into this community (also, see below).
  • Currently, the community is shattered over [Cross Validated](https://stats.stackexchange.com) and [Data Science](https://datascience.stackexchange.com). There is also a [sub-reddit](https://www.reddit.com/r/MachineLearning/) that is (at the time of writing) protesting against what Reddit is doing.
  • ### Additional Features
  • This community will definitely need support for **MathJax** and **code blocks**, but not sure if these are really additional.
  • Given that machine learning is becoming more and more well-known in non-technical contexts, it might be useful to set up a separate discussion zone where non-technical discussions, prompt engineering, ethics, etc. could get a place in the community.
  • This might make it possible to incorporate the [AI Tech proposal](https://proposals.codidact.com/posts/289124).
  • However, I didn't completely think this through yet.
  • I welcome any sort of feedback and/or suggestions for improvement!
  • The **Machine Learning** (ML) community aims to provide a platform for anyone interested in helping computers learn from data.
  • We mainly target people with backgrounds in data science, machine learning and data visualisation, but also statisticians, computer scientists and anyone looking to learn about the technical side of ML are more than welcome.
  • ### Topics
  • The goal would be to have a platform for technical (focus on math and/or implementation) questions about:
  • - supervised learning
  • - unsupervised/self-supervised learning
  • - deep learning and neural networks
  • - reinforcement learning
  • - data collection and pre-processing
  • - data visualisation
  • - data-driven computing
  • - applied statistics
  • - statistical learning theory
  • - predictive modelling
  • - Bayesian modelling
  • - applying ML models to data
  • - deployment of ML pipelines
  • - computational neuroscience
  • - prompt engineering
  • - ...
  • ### Off-Topic
  • To keep the community focused on ML, questions about the following topics should be asked elsewhere:
  • - pure coding questions (should be asked on software.codidact.com).
  • E.g. _How can I visualise this data with `matplotlib`?_ would be on-topic, but _How can I change the background colour of plots in `matplotlib`?_ should **not** be a question for this community.
  • - pure math and statistics questions (should be asked on math.codidact.com).
  • E.g. _What integrals do I need to compute the expectation of this random variable?_ would be okay, but _How do I compute this complex integral?_ would **not** be okay.
  • - system administration questions (should probably be asked on powerusers.codidact.com or linux.codidact.com).
  • E.g. _Are there any libraries that I can use to deploy my model using docker?_ is allowed, but _How do I set up docker?_ would **not** be suited.
  • - questions about other parts of Artificial Intelligence (AI) that have nothing to do with ML or ML algorithms. For these questions, a computer science community (cf. https://cs.stackexchange.com/) might be better suited.
  • E.g. _How does the AlphaZero chess engine learn to play chess?_ would be okay because AlphaZero involves learning, but _How can I build a chess engine using [alpha-beta pruning](https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning)?_ does not involve any ML and is therefore **not** suited for this community.
  • - requests for prompts or improvements to prompts for generating data (this requires a different kind of knowledge and is often considered to be the alchemy branch of ML).
  • E.g. _How does chain-of-thought prompting help the model to improve predictions?_ is a valid question, but _How can I fix this prompt for generating images with better lightning?_ is **not** okay.
  • - bug reports or other complaints about software (look for a bug tracker instead).
  • - questions about non-technical aspects of ML (e.g. opinions, ethics, legal, etc.).
  • - anything that is not (indirectly) related to machine learning.
  • ### Community Situation
  • Overlap on codidact will probably be mostly [software](https://software.codidact.com), [math](https://math.codidact.com) and [powerusers](https://powerusers.codidact.com)/[linux](https://linux.codidact.com) (as indicated above).
  • Maybe the [AI Tech proposal](https://proposals.codidact.com/posts/289124) could also be incorporated into this community (also, see below).
  • Currently, the community is shattered over [Cross Validated](https://stats.stackexchange.com) and [Data Science](https://datascience.stackexchange.com). There is also a [sub-reddit](https://www.reddit.com/r/MachineLearning/) that is (at the time of writing) protesting against what Reddit is doing.
  • ### Additional Features
  • This community will definitely need support for **MathJax** and **code blocks**, but not sure if these are really additional.
  • Given that machine learning is becoming more and more well-known in non-technical contexts, it might be useful to set up a separate discussion zone where non-technical discussions, prompt engineering, ethics, etc. could get a place in the community.
  • This might make it possible to incorporate the [AI Tech proposal](https://proposals.codidact.com/posts/289124).
  • However, I didn't completely think this through yet.
  • I welcome any sort of feedback and/or suggestions for improvement!
  • PS: I would greatly appreciate it if someone would have time/be interested to ask some questions on ML.
  • I tend to find it easier to answer questions than to ask them.
#1: Initial revision by user avatar mr Tsjolder‭ · 2023-08-01T19:34:48Z (over 1 year ago) 
Machine Learning
The **Machine Learning** (ML) community aims to provide a platform for anyone interested in helping computers learn from data.
We mainly target people with backgrounds in data science, machine learning and data visualisation, but also statisticians, computer scientists and anyone looking to learn about the technical side of ML are more than welcome.

### Topics

The goal would be to have a platform for technical (focus on math and/or implementation) questions about:

 - supervised learning
 - unsupervised/self-supervised learning
 - deep learning and neural networks
 - reinforcement learning
 - data collection and pre-processing
 - data visualisation
 - data-driven computing
 - applied statistics
 - statistical learning theory
 - predictive modelling
 - Bayesian modelling
 - applying ML models to data
 - deployment of ML pipelines
 - computational neuroscience
 - ...

### Off-Topic

To keep the community focused on ML, questions about the following topics should be asked elsewhere:

 - pure coding questions (should be asked on software.codidact.com).

   E.g. _How can I visualise this data with `matplotlib`?_ would be on-topic, but _How can I change the background colour of plots in `matplotlib`?_ should **not** be a question for this community.
 - pure math and statistics questions (should be asked on math.codidact.com).

   E.g. _What integrals do I need to compute the expectation of this random variable?_ would be okay, but _How do I compute this complex integral?_ would **not** be okay.
 - system administration questions (should probably be asked on powerusers.codidact.com or linux.codidact.com).

   E.g. _Are there any libraries that I can use to deploy my model using docker?_ is allowed, but _How do I set up docker?_ would **not** be suited.
 - bug reports or other complaints about software (look for a bug tracker instead)
 - questions about prompt engineering (because I believe the majority of technical people would consider this alchemy).
 - questions about non-technical aspects of ML (e.g. opinions, ethics, legal, etc.).
 - anything that is not (indirectly) related to machine learning.
 

### Community Situation

Overlap on codidact will probably be mostly [software](https://software.codidact.com), [math](https://math.codidact.com) and [powerusers](https://powerusers.codidact.com)/[linux](https://linux.codidact.com) (as indicated above).
Maybe the [AI Tech proposal](https://proposals.codidact.com/posts/289124) could also be incorporated into this community (also, see below).

Currently, the community is shattered over [Cross Validated](https://stats.stackexchange.com) and [Data Science](https://datascience.stackexchange.com). There is also a [sub-reddit](https://www.reddit.com/r/MachineLearning/) that is (at the time of writing) protesting against what Reddit is doing.

### Additional Features

This community will definitely need support for **MathJax** and **code blocks**, but not sure if these are really additional.

Given that machine learning is becoming more and more well-known in non-technical contexts, it might be useful to set up a separate discussion zone where non-technical discussions, prompt engineering, ethics, etc. could get a place in the community.
This might make it possible to incorporate the [AI Tech proposal](https://proposals.codidact.com/posts/289124).
However, I didn't completely think this through yet.

I welcome any sort of feedback and/or suggestions for improvement!
machine-learning