Explainable Artificial Intelligence (XAI) and interpretable machine learning with k-Lime+ELI5+SHAP+InterpretML In machine learning complex model has big issue with transparency, we don’t have any

# Machine Learning

## Interpretable machine learning LIME+ELI5+SHAP+InterpretML Python Code

In my previous article I discussed on Interpretable machine learning framework theory what their role and scope in Machine Learning, why they are important,

## Classification Algorithms Machine Learning and compare machine learning algorithms

Classification Algorithms Machine Learning and compare machine learning algorithms, As we know the Machine learning algorithm is divided into supervise and unsupervised learning. Classification

## linear regression machine learning python

linear regression machine learning python code used python library to do all the calculation which we have seen in the previous articles, Linear regression

## cost function in machine learning

The goal of Cost Function in Machine Learning is to start on a random point and find the global minimum point where the slope

## r squared formula

R Square formula value shows how close data point is to the fitted regression line, it also known as the coefficient of determination or

## ordinary least squares

Ordinary least square (OLS) or Lease square method in linear regression is mathematical analysis and its used to find the best fit line of

## linear regression machine learning

Linear regression machine learning establishes a relationship between two variable, is the way to find the changes dependent variable with respect to the explanatory

## Linear Regression Vs Logistic Regression

linear regression vs logistic regression (logistic vs linear regression) is a two important backbone algorithm for data science and machine learning regression models most of

## AI top 10 application for drawing

As we all know nowadays artificial intelligence, Machine Learning and deep learning daily introducing new mind-blowing application in the different sectors. In this article, we