Yesterday, I completed one more minor achievement on my own – I was able to receive enough upvotes on my works to receive a status of Kaggle Notebooks Expert. I’ve set it as a personal goal for myself for the end of this year, but thought that it is too optimistic (I will explain later why), and just continued ‘dancing as nobody sees it’.
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I decided to continue my journey with Kaggle and different datasets there, and to combine it with learning something new. While I used to check there some neutral datasets, and disappointed myself again with the inability to compose correct ML techniques on competitions, I still like to check what I can do with video games datasets, or try to extract some gaming-related stuff in common data sources.
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For last few weeks I’m obsessed with Kaggle: https://www.kaggle.com/ – a platform for data scientists, ML/AI engineers and data analysts. For significant share of people it is one of entry points in a machine learning world – just because of infinite variety of competitions, datasets, examples of notebooks and relatively strong community.
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