It is important to understand the different machine learning algorithms. Keeping abreast with the understanding of the algorithm can help the data science enthusiast understand their problem, their data set and the application procedure to derive the intended results.
We will start our discussion with Logistic Regression
Logistic regression is one of the popular mathematical modelling procedure which is used in many of the data analysis algorithms. It is basically a regression analysis where the value of the outcome variable (dependent variable) is restricted between 0 and 1. In order to achieve this, a logistic function is used which is the mathematical function on which the logistic model is based. The beauty of the logistic model is that the desired output value can be easily truncated within the comprehendible range of 0 and 1 irrespective of the range of output value.
If you are interested in how to apply logistic regression and the mathematical intuition behind it, you can express your interest in joining the data science boot camp for free by email to
