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Data Scientists must think like an artist when finding a solution, when creating a piece of code

Machine Learning can find patterns in the data that humans didn't see or couldn't fit into their stories. These are the best and most important observations for human understanding, because they reveal something new about ourselves.

Machine learning is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence.
Today, the importance of AI-ML is being felt in almost every domain. Therein arises the need for students to be AI-ML proficient. MLearning have arranged this workshop to create an awareness among students about a future in machine learning and to get students prepared for a bright career in machine learning // is made possible through the support of Fundacja św Anny

Great data scientists will never stop learning. If you think that you are done after 30 years, 40 years, if you think that you are done, some people think that they are done after just a few years. Well, you are absolutely not a good probably a very poor data scientist, because it's impossible even for a genius to have a complete picture to complete a career path in just a few years. There are so many things to know, so many possibilities to expand the boundaries and to increase the lateral thinking to to to to become more and more involved in the business, to be up to date in terms of technologies, to know more algorithms, to understand how it's possible to improve that learning is not a necessary it's a mandatory thing. So if you don't consider learning important for your work and if your employer don't consider learning important for your work, probably there's something wrong and a success can never be reached.



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TechCult #3 "Digital (AI) jungle"

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TechCult #2

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machine learning w przedsiębiorstwie produkcyjnym

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