Machine Learning Communities

Online communities are invaluable in machine learning, regardless of your skill level. The reason is that, like programming, you never stop learning. You simply cannot know everything, there are always new algorithms, new data and new combinations to discover and practice.

Communities help. You can get your questions answered, learn by answering other peoples questions and discover new areas from reading through the exchanges.

Machine learning communities have had a big impact on my education and in this blog post I want to list all of the online machine learning communities I know about so that you too can make the most of them.

machine learning communities

Machine Learning Communities
Photo by nadineheidrich, some rights reserved

Stack Exchange

The stack exchange sites are question and answer communities, so they are targeted towards problem solving. You can post the specific questions you have, answer questions to which you know the answer and (my favorite) read questions and answers to discover new methods and perspectives.

There are four sites I like to dip into:

  • Cross Validated: This site is useful for low-level questions on algorithms and statistical methods.
  • Quantitative Finance: (specifically the machine learning tag) This site is useful if you are operating in the financial domain, but generally if you are working with time series data.
  • Programmers: (specifically the machine learning tag) Great for specific code questions, such as a problem with a given library or tool you are using.
  • Stack Overflow: (specifically the machine learning tag) Again, like programmers, great for specific questions with the implementation side of machine learning. It’s also the oldest site and can cover machine learning algorithms and libraries.

There is a new site that has started up, but is still in beta, so it may not survive. It is called Data Science and I am finding it very interesting for the general concerns of applied machine learning (mix of code and math).


Reddit is a community of communities called sub-reddits. A given subreddit can be question and answer site, a link sharing site or (more typically) a mix of the two.

A few sub-reddits I frequent include:

  • Machine Learning: Contains of mix of “how do I get started” and more advanced links to machine learning blog posts. Also good for linking to your own projects to get some feedback.
  • Computer Vision: Mostly questions on computer vision questions both theoretical and practical (such as libraries).
  • Natural Language: Focus on natural language processing, providing a good mix of questions and links to relevant articles and blog posts.
  • Statistics: Discussion on statistical software and methods, great for digging deeper into a given method or algorithm.
  • Data Science: Mostly links to posts that straddle data analysis and machine learning.
  • Big Data: Focused posts and discussions on the big data ecosystem.

There are other sub-reddits on relevant and related topics, but I have not found them as useful.


Quora is a question and answer site that is divided into topics, much like reddit but only questions and answers. The questions are typically good and the answers high quality. Unlike the stack exchange sites, they are typically less technical, less problem focused and more meaty.

A few Quora topics I frequent include:

  • Machine Learning: Useful for high-level questions on algorithms, processes, resources and getting started. A good mix.
  • Statistics: Focus on deeper statistical methods and algorithms, but includes a lot of machine learning content.
  • Data Mining: Good questions with a focus on the applied side of machine learning, but a lot of overlap with Machine Learning.
  • Data Science: Much like the Data Mining and Machine learning topics, the questions are typically a higher level.

There are many other topics that might be useful, not limited to Data Analysis, Predictive Analytics, NLP and Computer Vision. Also there are topics on specific methods such as SVM, Deep Learning, Classification, and R.


There are some other great communities around that I could not classify as easily.

  • MetaOptimize Q+A: Like Cross Validated, this is a question and answer site that is great for lower level questions on specific algorithms and methods. Maths and theory heavy.
  • Kaggle Forums: Great for discussion around specific competitions and datasets, and full of great nuggets of advice for feature engineering, ensembling and refining your test harnesses.
  • DataTau: A social news site with a focus on links to posts on data and machine learning relate topics. Low traffic and useful links.


Some social media websites have machine learning groups. I don’t use these as much, but I mention them because you might find them useful than me.

There are some Google+ groups such as one on Machine Learning, R and Data Science. There does not seem to be definitive groups, but instead multiple competing groups around different topics.

There are also some LinkedIn groups that might be interesting, specifically, Data Mining and Machine Learning and the Machine Learning Connection. Again, like Google+ groups, there are multiple LinkedIn groups for a given area without clear leaders.

There used to be usenet groups I used to voraciously consume, but they all seem dead (or supplanted) these days.

In Person

Finally, consider communities in meat space. Take a look at a site like Meet Up and search for meet-ups in your area on subjects like machine learning, R, data analytics and data science. R user groups are typically a great place to learn and connect with professionals.

Do you know about another machine learning community? Leave a comment.

77 Responses to Machine Learning Communities

  1. Avatar
    Dean July 23, 2016 at 7:23 am #

    Nice collection, thanks Jason.

    We started newsletter about Artificial Intelligence startups, news and applications in industry. We would love if you join at

    We want to create value for everyone involved with Artificial Intelligence. Connect startups with breakthrough ideas and stakeholders in companies and across industries.


  2. Avatar
    Kwak Ji Won December 13, 2016 at 6:16 pm #

    I’m deep learning to doing research on researchers.
    I have previously supervised machine learning I mainly studied.
    These days I’m researching the online LDA (Linear Discriminant Analysis) learning to reduce dimensions of feature.
    But The function is provided in python scikit is offline LDA and is not provided LDA function similar to online SVM such as SGD (
    I do not find relevant data for the materials relating to online LDA on the Internet.
    If you know about it, I would appreciate your feedback.

  3. Avatar
    Edward Neol December 7, 2017 at 1:26 am #

    Customer Review of Book Machinelearning

    Practical Reinforcement Learning: Develop self-evolving, intelligent agents with OpenAI Gym, Python and Java

    Author has copy paste everything from other scientist approch

    Do not buy this book to waste your money

  4. Avatar
    Nadeer Petric December 7, 2017 at 1:27 am #

    See copy paste of content of this book.Why allows publishing these type of book to sell.

  5. Avatar
    Machine Learning February 7, 2018 at 3:58 pm #

    Nice and Simple but very useful article for Machine Learning Users/Learners.
    Thank you Jason Brownlee.

  6. Avatar
    Jesús Martínez April 23, 2018 at 6:29 am #

    Nice collection. Thanks.

  7. Avatar
    Thalanayar Muthukumar June 8, 2018 at 1:29 pm #

    Is there a forum where folks who are following the teachings here discuss in a forum?

  8. Avatar
    Minh Triet July 26, 2018 at 5:15 pm #

    MetaOptimize is down, there are also discord, slack and gitter, all serve same purpose.
    Slack: Computer Vision Slack group on r/computervision
    Discord: r/learnmachinelearning official Discord

  9. Avatar
    sanjay August 29, 2018 at 1:10 pm #

    Hi Jason,

    I want to train live streaming video for a frame of 8-10 seconds.image processing itself taking more than 2-3 days to train.i am trying to do it using opencv and tensorflow,but unable to do so.

    can you please help me

  10. Avatar
    Akash September 28, 2018 at 4:37 am #

    “meat space”? Isn’t that your refrigerator?

  11. Avatar
    Kiran October 8, 2018 at 6:52 pm #

    Thank you for sharing this wonderful information.

  12. Avatar
    Nazia November 24, 2018 at 12:25 am #

    Hi Brownlee,

    Your articles helped me a lot in my research work. I have a research question if you can guide me. It will be a great help. My question is

    What is the best way to compare the results of the proposed technique with existing if a different dataset is used?

    One cannot compare their proposed algorithm with others unless the same dataset is used. In case, a different dataset is used but the research problem is the same, what is the best way to compare the results of the proposed technique with existing?

    Thanks in advance.

    • Avatar
      Jason Brownlee November 24, 2018 at 6:35 am #

      Experimental results is a good way to compare algorithms. Computational complexity is another way.

  13. Avatar
    nbro February 24, 2019 at 12:57 am #

    I think you should update this post to include the website

  14. Avatar
    Python66 March 13, 2019 at 2:34 am #

    Respected Sir
    i am Little bit Confused about Learning algorithms hope i will get ans which will satisfy my curiosity
    (Question can be consider for Linear Regression)
    I want to know How ALGORITHM Learns
    As i know little bit about algos
    that can be made from a logic or we can say
    a mathematical logic or we can say any concept
    on which we want to Work

    like a very simple example is
    (In Pyhton)
    def see(z,y):
    return x

    A pure logical ans
    is this can’t be defined as learning,
    Ever next time in life when i will paas
    argument it will give me addition

    And same thing Linear Regression is Doing (Right)
    Taking Inputs giving ans on a certain condition

    LR=> h(x_i) = \beta _0 + \beta_1x_i

    But From where prediction=>(h(x_i)) & Learning Came
    Learning will be if it can give another ans
    related to my datasets which i didn’t defined
    in regression inside that Algorithm.

    Then may be someone can say that in learning Algos
    there is a part of Neural code(Neural Network)
    so firstly if i want to know How learning Works
    i have to Understand Neural Network


    With Gratitude

    • Avatar
      Jason Brownlee March 13, 2019 at 7:57 am #

      It iteratively devises the parametres of a mapping function from inputs to outputs that results in the lowest error.

  15. Avatar
    nStar March 18, 2019 at 7:52 pm #

    Thanks for sharing information about machine learning communities. These resources will certainly help students in achieving high degree of expertise in machine learning.

  16. Avatar
    Dhanji June 5, 2019 at 4:29 pm #

    Hi Jason,

    I am new in deep learning is below GPU good for deep learning.

    Please reply soon.

  17. Avatar
    Shiv June 13, 2019 at 8:36 pm #

    Hi Jason, I’m new to machine learning. I know basic python programming only. Could you guide me or suggest me where to start with machine learning.

  18. Avatar
    vijay July 10, 2019 at 8:15 pm #

    Wonderful. Thanks a lot for sharing machine learning communities. It is the need of the hour for students/learners

  19. Avatar
    Aslam July 17, 2019 at 12:27 am #

    Can anyone please suggest any algorithm to extract the signals after performing ICA on them. I have just mixture of signals coming from respective sites in certain order but after applying ICA the order gets mixed and I find it difficult to classify that which signal is for which site. So, can anyone suggest any algorithm that can do it automatically for me and tells me which signal is for which site?

  20. Avatar
    fatb September 14, 2019 at 12:00 am #

    Hi Jason

    what is the best format to feed the input data, which are time series with varying density over time, to a deep learning network, while at any iteration we want to feed a batch of data including a historical background?

    Is it better to consider a constant size of data records or a constant time window including variable data record size? Or is there a better way?

    Thanks in advance

  21. Avatar
    ML Developer January 8, 2020 at 11:19 pm #

    Hello Jason Thanks for sharing your article. I highly recommend your article. I am a ML developer . I am a Learner in this field. Please share more Machine learning communites with me. I want to add with these communities or forums.

  22. Avatar
    arun September 14, 2020 at 8:40 pm #

    Nice article. This article is great.
    You have solved my problems.
    I was finding genuine groups like these.
    Thanks for sharing.

  23. Avatar
    Sheena Rustomji November 4, 2020 at 10:00 pm #

    Thanks Jason. The guidance, you have provided on Machine Learning is top notch and defiantly will help someone.

    Just to refer few website which would help large audience to explore more Machine Learning Courses.

  24. Avatar
    Rik December 21, 2020 at 6:17 am #

    Nice overview Jason!

    I’m writing a blog in Dutch with lots of detailed and free Machine Learning tutorials. For people who speak Dutch this might be nice! We also organize meetups in the Netherlands.

    Some examples of tutorials:
    – Classification:
    – K nearest neighbor:
    – Linear Regression:
    – Support vector machine:

  25. Avatar
    John Morris January 10, 2021 at 9:08 pm #

    Hi, Jason! I hope you are doing well.

    When searching for online communities, there are a few things you should look for.

    The first is the type of learning environment you want. Are you mainly interested in learning by doing, asking questions and receiving answers, or do you prefer a more hands on learning approach with a heavy emphasis on code.

    The second thing to look for is the level of specialization. Do you like to know everything there is to know about a certain topic, or are you happy enough to know only the general basics.

    In my opinion, Quora no longer has the same activity that it used to be. I am interested in machine learning as well. I would love if you join and read

  26. Avatar
    Maheswari April 22, 2021 at 8:41 pm #

    Hi, jason… I have to classify the objects in realtime which has very little differences. How to do it using machine learning? Please suggest me some article or link to do it…

  27. Avatar
    Maheswari April 24, 2021 at 9:41 pm #

    Thanks for a reply

  28. Avatar
    Ramesh Sampangi April 29, 2021 at 12:44 am #

    Hi Jason, Thanks for sharing such a knowledgeable blog. Really well-written and informative content. Keep sharing.

  29. Avatar
    Swetha Venkatesh May 1, 2021 at 5:13 pm #

    Thank you for your help, connecting people who are keen to learn machine learning, This contains some of the blogs you give a read for gaining knowledge on ML. Hope you like it!

  30. Avatar
    Bhavani May 19, 2021 at 8:49 pm #

    nice information

  31. Avatar
    Alex May 28, 2021 at 5:50 pm #

    Thank’s, It’s a great thing that this article suggested the importance of Machine Learning Communities.

  32. Avatar
    social prachar10 June 7, 2021 at 3:36 pm #

    Nice article

  33. Avatar
    Swetha Venkatesh June 8, 2021 at 4:33 pm #

    I am very glad I can save this page and you have practically built a community on your page itself.

  34. Avatar
    snahta July 6, 2021 at 6:22 pm #

    nice post

  35. Avatar
    Brij Bhushan August 19, 2021 at 8:12 pm #

    I am glad to discover this page. I have to thank you for the time i spent on this especially great reading !! I really liked each part and also bookmarked you for new information on your site.

    • Adrian Tam
      Adrian Tam August 20, 2021 at 1:23 am #

      Thank you.

  36. Avatar
    Atul Raj January 11, 2022 at 8:26 pm #

    Machine Literacy is a system of data analysis that automates logical model structure. It’s a branch of artificial intelligence grounded on the idea that systems can learn from data, identify patterns and make opinions with minimum mortal intervention.

    • Avatar
      James Carmichael January 12, 2022 at 10:59 am #

      Thank you for the feedback Atul!

  37. Avatar
    Brij Bhushan February 12, 2022 at 4:22 pm #

    I also love your website because all type of information is available in your blogs. You made my day. Thanks you for everything. I have bookmarked more article from this website. Such a nice blog you are providing.

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