Machine Learning is an interdisciplinary field drawing from various information sciences such as computer science, statistics, mathematics, and engineering. According to Tom Mitchell, the author of Machine Learning, it is “the field of machine learning is concerned with the question of how to construct computer programs that automatically improve with experience.” This short definition is […]
Logistic Regression is a method to create Machine Learning model for two class problems. It came out of linear regression but used to generate binary output (0 and 1) for making classifications. For example In Linear Regression we use simple linear equation as follows :- Yh = b0 + b1X1 Where X combines linearly with […]
Decision Tree Classification Algorithm is used for classification based machine learning problems. It is one of the most popular algorithm as the final decision tree is quite easy to interpret and explain. More advanced ensemble methods like random forest, bagging and gradient boosting are having roots in decision tree algorithm. Here we will try to […]
KNN or K – Nearest Neighbours is one the powerful algorithm used in classification based problems to successfully make categorical predictions. Scikit-Learn gives us built in library to use and make the process easier for us if we are having data. But here we will write KNN code mathematically without any inbuilt library to figure […]
In every situation we went through numerous option same as here. Whenever we decided to work on ML, we do stuck into a thought process of selecting an algorithm which suits our need. Its also bit complicated to know all the minor details of each one of them. Then how can we decide X is […]