I am a beginner in GridSearch and need your help. I participate in Kaggle competition Home Credit. My knowledge is enough to make the right choice about right ML algorithm for my tasks (it's XGBoost). But I'm very disappointed about tuning parameters and choosing the right numbers for my model using GridSearch. Where can I find information in which order I need to tune parameters to achieve the maximum possible accuracy? Thanks!
There are several resources where you can learn something regarding Grid Search. For example: https://machinelearningmastery.com/grid-search-hyperparameters-deep-learning-models-python-keras/. But specifically for your case (tuning XGBoost) I think that these tutorials are better: https://towardsdatascience.com/fine-tuning-xgboost-in-python-like-a-boss-b4543ed8b1e https://www.analyticsvidhya.com/blog/2016/03/complete-guide-parameter-tuning-xgboost-with-codes-python/
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