Splitting a dataset into training and testing set is an essential and basic task when comes to getting a machine learning model ready for training. To determine if our model is overfitting or not we need to test it on…
Hello, readers! In this article, we will be focusing on How to Pull data from an API in Python. So, let us get started! Steps to pull data from an API using Python Let us now focus on the steps…
Hello, readers! In this article, we’ll talk about the different ways to connect and call APIs in Python. So, let us get started! What is an API? API is an acronym for Application programming Interface. It can be understood as…
Clustering is a technique of grouping similar data points together and the group of similar data points formed is known as a Cluster. There are often times when we don’t have any labels for our data; due to this, it…
In this article we’ll see how we can plot K-means Clusters. K-means Clustering is an iterative clustering method that segments data into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centroid). Steps for…
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.
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…