Deep Learning with Keras – Part 4: Classification

Classification Introduction Welcome to Part 3 of Deep Learning with Keras. The goal of this...

Regression with Keras (Deep Learning with Keras – Part 3)

Regression After two introductory tutorials, its time to build our first neural network! The network we are building solves...

Data Pre-processing for Deep Learning models (Deep Learning with Keras – Part 2)

Link to Part 1. Dealing with Data Motivation Training deep...

Logistic Regression With A Real-World Example in Python

In this tutorial, You’ll learn Logistic Regression. Here you’ll know what exactly is Logistic Regression and you'll also see an Example...

Deep Learning with Keras Tutorial – Part 1

About this series This post is the first part of Deep Learning with Keras series. This series aims to introduce...

Getting Started With Pytorch In Google Collab With Free GPU

In this post, we will discuss the basics of pytorch by using the google colab gpu

How to Connect Google Colab with Google Drive

In this tutorial, you’ll learn how to connect your Google Colab with Google Drive to build some Deep Learning model on Google...

Principal component analysis (PCA) using R

Principal component analysis (PCA) is a statistical analysis technique that uses an orthogonal transformation to convert a set of observations of possibly correlated variables...

Hierarchical clustering using R

Hierarchical clustering, also known as hierarchical cluster analysis, is an algorithm that clusters similar data points into groups called clusters. The endpoint is a...

R k-means clustering and evaluation of the model

The k-means clustering algorithms aim at partitioning n observations into a fixed number of k clusters. The algorithm will find homogeneous clusters. It works...