In Classification we will implement predicting sentiments,logistic regression using the sigmoid function based on maximizing log of likelihood, applying L2 regularization to it. Also, we will be building a Decision Tree model from scratch, a Binary decision tree from scratch, Precision Recall curves. We will also learn and implement ADA Boosting, Ensemble, Gradient Boosting and Stochastic Gradient
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In Classification we will implement predicting sentiments,logistic regression using the sigmoid function based on maximizing log of likelihood, applying L2 regularization to it. Also, we will be building a Decision Tree model from scratch, a Binary decision tree from scratch, Precision Recall curves. We will also learn and implement ADA Boosting…
yuwue2000/Machine-Learning-Classification
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In Classification we will implement predicting sentiments,logistic regression using the sigmoid function based on maximizing log of likelihood, applying L2 regularization to it. Also, we will be building a Decision Tree model from scratch, a Binary decision tree from scratch, Precision Recall curves. We will also learn and implement ADA Boosting…
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