“and” in Python Logical Operator

Python has three logical operators. The logical operator “and” in Python is used with two boolean operands and returns a boolean value. It’s also called a short circuit operator or boolean operator. We can’t overload “and” operator in Python. It only works with boolean operands. Logical Operator – and in Python Let’s say we have […]

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Python str() Function

Python str() function is one of the built-in functions. This function returns the string representation of the object. If there is no argument provided, it returns an empty string. Python str() Function Examples Let’s look at some simple examples of the str() function. How to implement str() function for an Object When we call the

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AVL Tree in Python: Complete Guide

In this article let’s understand the concept of the AVL Tree in Python; popularly known as the self-balancing binary search tree. The tree is named in honor of its inventors G.M.Adelson-Velsky and E.M.Landis. To understand the AVL tree thoroughly one should have the prerequisite knowledge of the binary search tree. The essential advantage of using

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Convex Hulls in Python

In this tutorial, we will walk through the implementation of a different and unique clustering approach with the help of convex hulls. But it’s always important to understand the concept before jumping right into the code! So let’s understand what convex hulls are. Introduction to Convex Hulls A Convex object is an object which has no interior

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Venn Diagrams in Python

The Venn diagram is one of the most obvious data visualizations for illustrating the overlap between two or three data categories or “sets.” John Venn designed these diagrams in the late 1800s; they depict each set of data in a circle, with the overlap signifying the degree of resemblance between the groups. You might have

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Support Vector Machines in Python

When it comes to the implementation of Machine Learning algorithms, the list starts from linear regression to decision trees. They are of various types. Mainly when it comes to separations of data points along a linear axis the recommendations from the experts are: K-means clustering. Support Vector Machines. As we all know that an ML

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