# Category Archives: Machine Learning

## Complement Naive Bayes (CNB) Algorithm

Naive Bayes algorithms are a group of very popular and commonly used Machine Learning algorithms used for classification. There are many different ways the Naive… Read More »

## Components of Linear Algebra

Linear algebra is actually branch of mathematics but it is the mathematics of data that provides mathematical framework for solving problems. This framework is especially… Read More »

## Top Python Notebooks for Machine Learning

Notebooks illustrates the analysis process step-by-step manner by arranging the stuff like text, code, images, output, etc. This helps a data scientist record the process… Read More »

## What is SageMaker in AWS?

Machine Learning is the hottest topic in the current era and the leading cloud provider Amazon web service (AWS) provides lots of tools to explore… Read More »

## Wilcoxon Signed Rank Test in R Programming

The Wilcoxon signed-rank test is a non-parametric statistical hypothesis test used to compare two related samples, matched samples, or repeated measurements on a single sample… Read More »

## Top 10 Business Intelligence Platforms in 2020

Business Intelligence platforms are extremely important for businesses to remain relevant in this competitive market. They fulfill multiple functions for businesses including understanding the consumer… Read More »

## Bidirectional Associative Memory (BAM) Implementation from Scratch

Prerequisite: ANN | Bidirectional Associative Memory (BAM) Learning Algorithm To implement BAM model, here are some essential consideration and approach- Consider the value of M,… Read More »

## ANN – Bidirectional Associative Memory (BAM) Learning Algorithm

Prerequisite: ANN | Bidirectional Associative Memory (BAM) There are three main steps to construct the BAM model. Learning Testing Retrieval Each step has been described… Read More »

## Pearson Correlation Testing in R Programming

Correlation is a statistical measure that indicates how strongly two variables are related. It involves the relationship between multiple variables as well. For instance, if… Read More »

## Deep Convolutional GAN with Keras

Deep Convolutional GAN (DCGAN) was proposed by a researcher from MIT and Facebook AI research .It is widely used in many convolution based generation based… Read More »

## 5 Best Books to Learn Data Science in 2020

Data Science is one of the in-demand technologies of 2020 and if we wish to learn and make a career out of it, then there… Read More »

## Cycle Generative Adversarial Network (CycleGAN)

CycleGAN was proposed by. It is used to transfer characteristic of one image to another or can map the distribution of images to another. In… Read More »

## Variational AutoEncoders

Variational autoencoder was proposed in 2013 by Knigma and Welling at Google and Qualcomm. A variational autoencoder (VAE) provides a probabilistic manner for describing an… Read More »

## Histogram of an Image

The histogram of a digital image with gray levels in the range [0, L-1] is a discrete function. Histogram Function: Points abut Histogram: Histogram of… Read More »

## Kolmogorov-Smirnov Test in R Programming

The Kolmogorov-Smirnov Test is a type of non-parametric test of the equality of discontinuous and continuous of a 1D probability distribution that is used to… Read More »