Vectorized implementation of cost functions and Gradient Descent

Linear Regression

1. Ordinary least square or Residual Sum of squares (RSS) — Here the cost function is the (y(i) — y(pred))² which is minimized to…

AI Mind Map

Hypothesis testing : p value method

p value can be interpreted as the probability that the null hypothesis is correct. So higher the…

Hypothesis testing — Critical Value Method

Unlike the inferential statistics, hypothesis testing is about confirming a…

Precision and Recall

Imagine there is a class of 18 students, in which 8 students are genius in reality. And 10 students are not genius. Say, we develop a model to classify the students into two labels — “Genius” and “Not Genius”. Now, we would like to evaluate this model. To evaluate any such binary classifiers…

Confidence Interval & Confidence Level

I) IDENTIFYING CONFIDENCE LEVEL GIVEN CONFIDENCE INTERVAL

Sampling Distribution

1. Whenever ‘distribution’ word is used, it is generally referred to probability distribution function (PDF). The x-axis of…

Evaluating a model on overfitting and underfitting

Ofcourse if there is more than one independent variable it is difficult to visualize the underfit or overfit. But then, this can be inferred if you plot the “Learning Curve”.

Linear Regression Model

Linear regression Model is a supervised learning algorithm in which we try to predict a linear equation with one or more than one independent variables. Given the independent variables, the equation is able to predict the dependent variable. The independent variables are known as…