Yeah I don't think I agree with the assessment that better models are a function of finding better hyper parameters (entirely). Like, in my limited experienced,

Yeah I don't think I agree with the assessment that better models are a function of finding better hyper parameters (entirely). Like, in my limited experienced,stacking and packing models (the 'lift' required by individual models), adjusting ones thinking regarding 'how' they go from data-in >> product out and 'what' it is were trying to predict, pipe-lining annotation and scaling its distribution, are far more effective at generating better ML models than tuning hyper parameters. Generally, if a model is not performing or generating unexpected results, its almost always the data or how the question is being structured.