I did some self-study to learn Neural network, object detection, and deep learning. Now I started implementing YOLOv3. I am looking for some website that I can communicate with people and make friends who are learning and implementing deep learning algorithms like me. It will speed up my learning since self-studying gets boring sometimes.

I was wondering if you could introduce some website that I can find peoples like myself.

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    $\begingroup$ Please don't close this question. I know, it is heavily opinion based and thus not a good fit for SE, but I think a lot of people have the same question. We can use this as a reference for future questions which are more about discussion / opinions than about facts. $\endgroup$ – Martin Thoma Nov 19 '18 at 6:34
  • $\begingroup$ @MartinThoma Not because it is useful it should not be closed. If it's off-topic, it should be closed. This question is better suited for Quora, e.g. $\endgroup$ – nbro Nov 19 '18 at 11:27
  • $\begingroup$ @nbro AI can't be discussed without referencing to people who are involved in the subject. On the first hand, these people are located within universities, but also in companies deeplearning problems are under investigation and last but not least, many amateurs are interested. Each of these groups has a different approach in learning the topic, for example in a scholarly background a formal title is important while in amateur context the focus is on getting instant feedback by peers. $\endgroup$ – Manuel Rodriguez Nov 19 '18 at 12:02

I highly recommend to get a local peer group. Meetups might be a good way to get to know some people. As a student at university you also have a lot of other options like going to lectures, creating a student group, organizing a local AI event / hackathon, ...

If this is not possible for you, here is what you can do online:

  • Reddit: r/deeplearning seems to have a couple of discussions. r/MachineLearning is cool if you want to discuss super recent stuff, but I would not say it is beginner level.
  • Google+
  • Coursera: if you take one of their courses, you will see a forum for discussions
  • $\begingroup$ The Google+ URL can be ignored, the community has lost the race against Facebook. The Reddit link looks promising, because there are many people (according to the stats 22.9k) on the website. But Reddit is not involved in higher education and provides mostly snippet videos. For example, a company who want's to sell their hardware are posting a new youtube video about how wonderful the new accelerator is, or another company who wants to sell their online courses are providing information how happy the user are. $\endgroup$ – Manuel Rodriguez Nov 19 '18 at 8:39
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    $\begingroup$ @ManuelRodriguez There are some cool topics on the reddit (at least this one, I don't know for deeplearning : reddit.com/r/MachineLearning ), like dicussing new papers and so on.... Of course this is not only highly educated, but there are a lot of discussions about research that can be useful ! also, people share new ideas that can be helpful to discover new topics on machine learning. $\endgroup$ – Jérémy Blain Nov 19 '18 at 8:46

The main categories that answer the question have many tributes.

  • Academia
  • Industry
  • Social networks

Here are some of the options that roughly fit into these options which have not yet been mentioned in answers.

  • For those not registered as students, several university clubs are open to non-student members
  • For those registered as students, several university professors would be willing to be the faculty adviser for a student led AI club and possibly excited about it
  • FaceBook has several AI related groups
  • YouTube has channels related to AI
  • IEEE membership can be of benefit, and it is inexpensive if you are a registered student
  • Association for Computing Machinery at acm.org, founded in 1947, and is the world's largest scientific and educational computing society

Communing with those that have more experience should not be dismissed. Some are looking to foster expertise in beginner enthusiasts.

  • Get a job in the field and finding people that will consider friendships that begin in professional environments
  • Offer assistance at an AI lab, even if that means menial gofer tasks at first, such as blogging to drive web traffic to their site or most recent publication
  • Attendance at AI events online
  • Travel and stay overnight at major AI events, attend the networking breakfasts, evening events, visit the exhibits, and bring business cards

Here in this AI StackExchange, ongoing dialog is prohibited in the main Q&A comments, but there are conversations in the space provided for that. As it develops, a kind of community forms, and it has been maturing. People get appreciative, annoyed, overly competitive, repentant, collaborative, friendly, inspired in their writing, and seeded with new ideas and understanding every day.

Some people here occasionally ask to communicate outside this space or freely use their real names and photos. Use discretion, but there is no rule against furthering contact if the feeling is mutual that I could find in the Help Center.


In my opinion, computer science in general, not only artificial intelligence, is learned by doing.

Basically, You work on your project, you face problems (like memory management, security (yes there are security issues in AI), neural network training speed or efficiency). You post your code snippets here on stackexchange, and people will help you out.

That would be considered as a technical discussion, and I think it is more important than talking broadly about a subject that is meant to be very specific and detailed.

As others mentioned, you can find some good communities on reddit, and in different AI related topics, and people there are mostly geeks who would spend hours talking about the subject.

Or, if you do not find what you need, go ahead and create your new community.

There is also another option, yet one that I recommend, create a personal website, whenever you learn something new or have a new insight, write an article and make it possible for people to add comments and discuss the subject at hand. Always archive what you learn, your website will be like a reference or archive where you organize your knowledge.

Another option I recommend You actually can consider creating a medium.com account for this, and start writing about what you know right now, then you will start to make loyal readers with whom you can discuss whatever comes to mind.

Finally, if you want to study with other people, then here is an idea : search for beginners with ai related profile on linkedin , and send some messages asking them to join you, I do not think most beginners, who also want to study and learn more, will refuse.

Edit : And I forgot github.com or gitlab.com. Where people can view your code, and even work with you as a team. I highly recommend gitlab as you can create private repositories for free.

Among others, and once you find 2 or 3 interested people on linkedin, you can work together on skype, google hangouts.

Notice I do not recommend facebook, I personally tried it to chat with a team of developers, and it ended up being an element of distraction, none was really focused on the subject at hand.

Wish you the best.

  • $\begingroup$ And I forgot github.com (or gitlab.com) .. where people can view your code, and even work with you as a team. $\endgroup$ – SmootQ Nov 19 '18 at 9:49
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    $\begingroup$ you can edit your post if you forget somes informations ! $\endgroup$ – Jérémy Blain Nov 19 '18 at 9:51
  • $\begingroup$ According to the answer, the knowledge about neural networks is located within chatrooms, personal websites and adhoc online-discussions. That means, a beginner starts with zero knowledge and connects to other which have also zero knowledge. This ideology won't be successful, because knowledge has to written down and new contributors have to add information to existing sources. Describing community building as a face-to-face communication problem will ignore the gutenberg galaxis and the printing press. $\endgroup$ – Manuel Rodriguez Nov 19 '18 at 10:01
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    $\begingroup$ @ManuelRodriguez This answer is a great answer FOR the question asked. Chats with beginners doesn't mean that they have ZERO knowledge. that just means they have maybe a few knowledge and want to discuss about topics and grows a little beginner community to leanr together and get motivated. Looking for Arxiv papers all day is not motivating at all, even if it sometimes necesssary. This is not the only way to learn. $\endgroup$ – Jérémy Blain Nov 19 '18 at 10:05
  • $\begingroup$ The OP is not a total beginner with zero knowledge, he says that he already started implementing YOLOv3. $\endgroup$ – SmootQ Nov 19 '18 at 10:05

There are a few options.

  • Social networks that have groups
  • Associations that seek members
  • University clubs that do not require members be registered for classes
  • Conferences
  • Corporations with organizations that seek members

Here are just a few of many.


Apart from SE.AI itself, a valuable alternative to discuss deep learning with beginners is the academic sphere, namely Arxiv and similar websites. The H-index as the result of citing each other can be seen as a friendship indicator. If somebody was often mentioned in the reference section he has many scholars as a friend. People, who are involved in Academia (phd students and professors), are uploading papers to Arxiv, and in the articles they are referencing to papers written before to discuss deeplearning topics. It is a bit complicated to post something to a journal, but at least in the reading mode the service is great. Higher education (which are universities and scholarly journals) are the traditional place to discuss deep learning topics. And most information about the subject are generated by the scholarly community. Even if somebody is not located near to classical universities he can't ignore it. The reason is, that most papers and most books are created by scholarars. Open up the traditional system for new members is called Open Science. Concrete questions about the YOLOv3 detector, which is an addon to OpenCV, are ontopic at Stackoverflow which has around 1k questions about it. In contrast to Arxiv, Stackoverflow is open to everybody as default and is the most widely used website for programmers.

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    $\begingroup$ "a valuable alternative to discuss deep learning with beginners is the academic sphere, namely Arxiv and similar websites" yeah but you can't discuss on this websites..... $\endgroup$ – Jérémy Blain Nov 19 '18 at 8:45
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    $\begingroup$ OP is: "... looking for some website that I can communicate with people and make friends who are learning and implementing deep learning algorithms like me" - i.e. wants to find fellow students and interact with them, not access more study material. $\endgroup$ – Neil Slater Nov 19 '18 at 9:03
  • $\begingroup$ Arxiv is one of the best sources out there. $\endgroup$ – SmootQ Nov 19 '18 at 10:17
  • $\begingroup$ @SmootQ Correct. And the OP did not ask for sources, but for a place to have discussions. $\endgroup$ – Martin Thoma Nov 19 '18 at 12:06
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    $\begingroup$ @ManuelRodriguez The title of the question is "Where can I discuss with deep learning beginners?". In the journals (and more importantly the conferences like NIPS, ICML, ICLR, ICCV, ...) which are worth something are not for beginners. $\endgroup$ – Martin Thoma Nov 19 '18 at 13:07

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