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…
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…
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…
Today we look at a very famous method called the Monte Carlo, which can be used to solve any problem having a probabilistic interpretation.
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…
Hello, readers! In this article, we will be focusing on the Understanding and Implementation of KNN in Python. So, let us get started!! What is KNN Algorithm? KNN is an acronym for K-Nearest Neighbor. It is a Supervised machine learning…
Welcome. Today, we are going to cover how to build a basic single perceptron neural network. I want to make this the first of a series of articles where we delve deep into everything - CNNs, transfer learning, etc. so be sure to bookmark the site and keep checking it. Also, this will include a lot of math, so strap in.
Hello, readers! In our series of Data processing and analysis, today we will be having a look at Detection and Removal of Outliers in Python. So, let us get started! What are Outliers in Python? Before diving deep into the…
We’ve already worked on PCA in a previous article. In this article, let’s work on Principal Component Analysis for image data. PCA is a famous unsupervised dimensionality reduction technique that comes to our rescue whenever the curse of dimensionality haunts…