How Generative Adversarial Networks (GANs) work?

Generative Adversarial Networks were first introduced in 2014 in a research paper. They have also been called  “the most interesting idea in...

A Few Things To Remember Before Going To Start a Data Science Course

Over the last few years, the data science domain has evolved exponentially. In present times, it has become the backbone of many...

List of Data Science and Machine Learning GitHub Repositories to Try in 2019

Here is the list of selected Data Science and Machine Learning GitHub Repositories to Try in 2019 Paper with...

5 Must Excel Add Ins​​ For Data Science Practice

Below is the list of five important Data Science practice add-ins used in Microsoft Excel. 1. Power Pivot: Power Pivot...

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...

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...

List of Data Science Books to Read

Here is the list of recommended data science books for reading: Numsense! Data Science for the Layman: No Math Added by Annalyn Ng and...

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...

What Personal Data do Navigation Apps Collect?

The tradeoff between convenience and privacy continues to grow in importance as technology becomes more intertwined in our lives. Tech giants like...

Regression using Tensorflow and multiple distinctive attributes

As we did in the previous tutorial will use Gradient descent optimization algorithm. Additionally, we will divide our data set into...

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