Day-15 of Machine Learning:
- Implemented Sigmoid function, cost function, Gradient descent for logistic regression for Logistic Regression and a prediction function with 0.5 threshold to build a logistic regression model to predict whether a student gets admitted into a university.
- Also implemented regularized logistic regression to predict whether microchips from a fabrication plant passes quality assurance (QA) where I implemented cost function and gradient descent for Regularised Logistic Regression.
With this I completed Course-1: Supervised Machine Learning: Regression and Classification
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