Mathematica has a question that is very useful for beginners:
What are the most common pitfalls awaiting new users?
For me as a beginner who wants to use artificial intelligence applications in remote sensing and is familiar with MATLAB, C++ and a little JAVA.
There is always a question which open source or non open source libraries and APIs are there to implement an algorithm (for example which library can be used for implementing simulated annealing in C++, What libraries are there to implement wavelet transformation in C++) in a specific programming language and I have seen such questions in research gate a lot.
For example someone has asked Which library is recommended for AI programming with Python?
Such question is not allowed here because of being primarily opinion-based but I think we can have a reference instead considering all those conditions for a reference question:
- One topic per answer .
- Focus on non-advanced uses (it's intended to be useful for beginners and as a question closing reference).
- Include a self explanatory title in h2 style.
- Explain the symptoms, the mechanism behind the scenes and all possible causes and solutions you can think of. Be sure to include a beginner's level explanation (and a more advance one too, if you're in the mood) .
- Include a link to your answer by editing the Index below (for quick reference).
For example in an answer someone introduces all open source or non open source libraries that can be used to implement Bee colony algorithm in C++, lisp, prolog, etc together with advantages and disadvantages of each API.
In another someone introduces APIs to implement SVM classifier in MathLab, C++, etc with its advantages and disadvantage.
Do you think it can be a good fit for this site?