Welcome, this page is devoted to General Algorithms, Machine Learning, and 3D-modeling.
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In my job experience as an academic and industry mathematician, I observed that the majority of academic mathematicians focus too much on highly specific topics that not many people in the world understand. This is especially true in pure mathematics. Even in applied mathematics, developing a new algorithm (for the purpose of publication if you are an academic) that can beat an existing algorithm can be extremely hard and realistically/practically, not worth pursuing.
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Here I will present some useful algorithms. Algorithms that you don't necessarily learn when studying Mathematics, Applied Mathematics, or when doing advanced mathematical research. For a person with a math degree, it's important to learn how to use these algorithms properly, since your job options outside of teaching or academia will probably include some coding, if you are lucky, or working at a lower paying jobs if you are unlucky. I would advise the reader who is currently studying mathematics and whose goal is academia to supplement your degree with more practical courses and/or be prepared to set aside a significant amount of time to learn more practical skills for your employment opportunities. Do projects that are of actual interest to the wider population. If you are a Ph.D. like me, only a few people in academia will understand your work and will likely not recommend/hire you for a postdoc position, let alone tenure track. It could be difficult to get an industry job or pass the easy/early-stage technical interviews for an industry job with the impractical skillsets that you spent most of your life as an academic studying.
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Thus, the main goal of this page is to inform the reader who wants an academic career to hedge your job opportunities now. When I have time, I will post information on practical use of data structures, algorithms, machine learning, and 3-dimensional modeling applications that are currently in use in industry jobs.
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