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im sorry if i sounded rude. I am a self learning noobie in the world of data science. ive seen many youtube tutorials and thus i cam to a conclusion that nenural networks generally work well when compared to the other approaches. for the matter of fact. NN giving such poor performance just swept me off a little. i know im going wrong somewhere. its just that i learn from these type of silly mistakes.
hi i have already implemented other machine learning models like random forests, Gradient boosting and Näive Bayes where i got an accuracy of 95%, 93% and 78% respectively. the reason why im so particular about NN is that. im experimenting stuff ie: trying different models. so i just want to know where i am going wrong because what i've seen/heard is that Neural networks should actually work better comparatively. not better than the rest but atleast a very good performance.
