APPLICATION OF SUPERVISED LEARNING
MACHINE LEARNINGHARD QUESTIONS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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That is at least 95% accurate on the training data set
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That is at the sweet spot between a simple working model and a very complex one
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That makes you feel like you are a true machine learning expert
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That takes less than 30 minutes to train and validate
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Detailed explanation-1: -Tuning is the process of maximizing a model’s performance without overfitting or creating too high of a variance. In machine learning, this is accomplished by selecting appropriate “hyperparameters.” Hyperparameters can be thought of as the “dials” or “knobs” of a machine learning model.
Detailed explanation-2: -Grid search is arguably the most basic hyperparameter tuning method. With this technique, we simply build a model for each possible combination of all of the hyperparameter values provided, evaluating each model, and selecting the architecture which produces the best results.
Detailed explanation-3: -Grid Search This method tries every possible combination of each set of hyper-parameters. Using this method, we can find the best set of values in the parameter search space.