Top Q&A Forums for AI and ML Practitioners

Data scientists work on a variety of complex business problems, using statistical knowledge as well as multiple tools. When stuck on something, a data scientist can’t afford to wait days to figure out how to move forward. A forum where like-minded people from the same profession participate in helping each other can come to the rescue. Popular forums bring together experts from all over the world who actively participate in healthy discussions, resolve doubts and impart their knowledge to others. Let’s take a look at some of these Q&A forums that all AI and ML practitioners should attend.

Reddit: Machine Learning

Reddit is one of the most popular communities that one can explore to solve their queries. This particular machine learning community has about 2.4 million members. Posting on Reddit has the advantage of having extremely fast responses because members are very active on the platform. The machine learning community discusses topics regarding the latest in machine learning, job vacancies, project doubts, and more. There are also similar groups for deep learning, NLP and computer vision.

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Picture: Machine Hack

The MachineHack discussion forum is also a great place to post your doubts. It has a very active and engaging community, and users can get answers to all technical challenges in machine learning, artificial intelligence, data engineering, and data science, among others. It also has an assessment section where one can take tests to gauge their skills in cloud technologies, machine learning, programming languages, and more. There is another section in MachineHack to prepare you for your interviews for roles like Data Engineer, ML Engineer, Scientist, etc.

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Kaggle is generally a favorite among data scientists. It contains large datasets that data scientists can work with, build models, and get a sense of the real world. Kaggle also contains a very active forum to discuss all your analytics-related doubts. Highly recognized experts are also very active on Kaggle, and one can get answers to their questions from some of the most successful professionals in the field. Discussions can range from basic to advanced topics in NLP, computer vision, neural networks, visualization and more.

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StackOverflow says that so far, more than 21 million questions have been asked on its platform, with 13.6 seconds being the average time between new questions. StackOverflow is famous for its Q&A platform which sees over 100 million traffic every month to ask questions, learn, and share technical knowledge. It has a vibrant AI, analytics, and machine learning community.

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IBM Global Data Science Forum

Picture: IBM

IBM has different communities to share and discuss their know-how on IBM products. The Global Data Science Forum has approximately 21,000 members, 223 libraries, and 556 blog posts. IBM also has a business analytics community where one can get product updates and analyze their AI skills. A DataOps community is also in place. Some areas of discussion include Data Replication, DataStage – Data Integration, Global DataOps, Master Data Management (MDM), Watson Knowledge Catalog (WKC), Data Governance and Quality, etc.

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Discussion Forum – Data Science Central

Data Science Central is a forum for Big Data practitioners. It features technical topics that delve into specialist knowledge of technical aspects of data science and business topics with an emphasis on sector-specific topics associated with a specific industry. It also has a section on programming languages ​​that covers coding techniques in various languages.

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Harry L. Blanchard