ML(머신러닝) :: The problem of overfitting
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. 1. Example 1: Linear regression for housing prices 1.1 Underfitting (high bias) We
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. 1. Example 1: Linear regression for housing prices 1.1 Underfitting (high bias) We
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. Let’s see how to fit Θ for Logistic regression. To do so, We
Read MoreML(머신러닝) :: Logistic regression – Cost Function(비용함수)
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. In the post that contained contents on Linear regression, We learned how to use
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. 1. Hypothesis Representation We’re going to use hypothesis representation to represent the hypothesis
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. 1. Classification problems ex) E-mail: Spam or Not Spam ex) Tumor: Malignant(positive class, 1)
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. 1. define a matrix >> t = [0:0.01:0.98]; 2. plot >> y1 = sin(2*pi*4*t)
What is Feature Scaling? 1. Feature Scaling When each feature has a similar scale or similar ranges of values, Gradient Descent converges much faster. Therefore, It is possible to
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. From now on we are going to learn about the new version of Linear
Read MoreML(머신러닝) :: Linear Regression with Multiple features
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. 1. Gradient descent So far, We used Gradient descent to solve linear regression problems.
Contents in the post based on the free Coursera Machine Learning course, taught by Andrew Ng. 1. Supervised Learning There are numerous Machine learning algorithms like reinforcement learning, recommender
Read MoreML(머신러닝) :: Supervised Learning VS Unsupervised Learning