# Abhishek Wasnik

## Pandas Pivot Tables in Python – Easy Guide

In this article, we’ll talk about Pivot Tables in Python. We’ll implement the same using the pivot_table function in the Pandas module. What is a Pivot Table? Pivot Tables are a key feature of Microsoft Excel and one of the reasons that made excel so popular in the corporate world. Pivot tables provide great flexibility …

## K-Fold Cross-Validation in Python Using SKLearn

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 unseen data (Validation set). If a given model does not perform well on the validation …

## Hierarchical Clustering with Python

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 becomes very difficult to draw insights and patterns from it. Unsupervised Clustering techniques come into …

## Matplotlib Subplots – Plot Multiple Graphs Using Matplotlib

In this article, we will learn how to create Matplotlib subplots. In practice we often need more than one plot to visualize the variables, this is when subplots come into the picture. Matplotlib subplot method is a convenience function provided to create more than one plot in a single figure. Creating a Basic Plot Using …

## Normal Distribution in Python

Even if you are not in the field of statistics, you must have come across the term “Normal Distribution”. A probability distribution is a statistical function that describes the likelihood of obtaining the possible values that a random variable can take. By this, we mean the range of values that a parameter can take when …

## How to Plot K-Means Clusters with Python?

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 Plotting K-Means Clusters This article demonstrates how to visualize the clusters. We’ll use the digits …

## Naive Bayes Classifier with Python

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 …

## Principal Component Analysis from Scratch in Python

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 …

## Principal Component Analysis For Image Data in Python

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 us. Working with image data is a little different than the usual datasets. A typical …

## Density Plots in Python – A Comprehensive Overview

A density plot is used to visualize the distribution of a continuous numerical variable in a dataset. It is also known as Kernel Density Plots. It’s a good practice to know your data well before starting to apply any machine learning techniques to it. As a good ML practitioner we should be asking some questions …