Python Tutorials and Examples

A treemap in Python is a visualization of data that splits a rectangle into sub-parts. The size of each subpart is in proportion to the data it represents. It is somewhat like a pie-chart. Although, treemaps can represent much-more complex data as compared to a pie-chart. It can help you visualize how single values compose […]

Naïve Bayes Classifier is a probabilistic classifier and is based on Bayes Theorem. In Machine learning, a classification problem represents the selection of the Best Hypothesis given the data. Given a new data point, we try to classify which class label this new data instance belongs to. The prior knowledge about the past data helps

Quicksort is a sorting algorithm that follows the policy of divide and conquer. It works on the concept of choosing a pivot element and then arranging elements around the pivot by performing swaps. It recursively repeats this process until the array is sorted. In this tutorial we will learn how QuickSort works and how to

Today we look at a very famous method called the Monte Carlo, which can be used to solve any problem having a probabilistic interpretation.

Principal component analysis or PCA in short is famously known as a dimensionality reduction technique. It has been around since 1901 and still used as a predominant dimensionality reduction method in machine learning and statistics. PCA is an unsupervised statistical method. In this article, we will have some intuition about PCA and will implement it

What is Gradient Boosting?
extreme Gradient Boosting, light GBM, catBoost

A simple number cannot represent your dataset? How about setting your variable value to infinity in Python? Today we’re talking about just that! While coding in Python, we often need to initialize a variable with a large positive or large negative value. This is very common when comparing variables to calculate the minimum or maximum