Logistic Regression is one of the most popular Machine Learning algorithm used for the classification problems. It should be noted that though there is a regression word in the name of the algorithm Logistic Regression, it is used for classification problems. A use case of Logistic regression could be, based on the symptoms for a disease that a patient has Logistic … Continue reading Implementing Logistic Regression in 10 lines in Python

# Machine Learning

# Top 5 Advantages and Disadvantages of Support Vector Machine Algorithm

Support vector machines or SVM is a supervised machine learning algorithm that can be used for both classification and regression analysis. Advantages of Support Vector algorithm Support vector machine is very effective even with high dimensional data.When you have a data set where number of features is more than the number of rows of data, … Continue reading Top 5 Advantages and Disadvantages of Support Vector Machine Algorithm

# Top 6 Advantages and Disadvantages of Decision Tree Algorithm

Decision Tree is one the most useful machine learning algorithm. Decision tree can be used to solve both classification and regression problem. When we use data points to create a decision tree, every internal node of the tree represents an attribute and every leaf node represents a class label. Like any other machine learning algorithm, … Continue reading Top 6 Advantages and Disadvantages of Decision Tree Algorithm

# Linear Regression using sklearn in 10 lines

Linear regression is one of the most popular and fundamental machine learning algorithm. If relationship between two variables are linear we can use Linear regression to predict one variable given that other is known. For example if we are researching how the price of the house will vary if we change the area of the … Continue reading Linear Regression using sklearn in 10 lines