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All Blog Posts Tagged 'dsc_visualize' (37)

Voice Cloning: Corentin's Improvisation On SV2TTS

Working with the audio production and engineering industry, I often wonder how the future of the voice talent market will look like with the assistance of artificial intelligence. The development of cloning technology started a while back but it did not reach today's level overnight. The debate of misusing this…

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Added by Mahmud Hossain Farsim on February 17, 2021 at 6:00pm — No Comments

Beautiful Mathematical Images

To zoom in on any picture, click on the image to get a higher resolution.

Figure 1: The pillow basins (see section 3)

The topic discussed here is closely related to optimization techniques in machine…

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Added by Vincent Granville on February 2, 2021 at 10:30am — 1 Comment

Can Smart Data Visualization Help My Business Users?

If you want your business users to have access to analytics tools that are easy enough for the average user to understand, you will want to select augmented analytics that are easy to use with guidance and recommendations to help the user achieve the results they want AND help the user understand those results once they finish the…

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Added by Kartik Patel on February 1, 2021 at 2:56am — No Comments

Deep visualizations to Help Solve Riemann's Conjecture

This is the second part of my article Spectacular Visualization: The Eye of the Riemann Zeta Function, focusing on the most infamous unsolved mathematical conjecture, one that has a $1 million dollar price attached to it. I used the word deep not in the sense of deep neural networks, but because the implications of these…

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Added by Vincent Granville on January 5, 2021 at 9:00pm — No Comments

Spectacular Visualization: The Eye of the Riemann Zeta Function

We discuss here one of the most famous unsolved mathematical conjectures of all times, one among seven that has a $1 million award attached to it, see here. It is known as the Riemann Hypothesis and abbreviated as RH. Of course I did not solve it (yet), but the material presented here offers a new…

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Added by Vincent Granville on January 2, 2021 at 11:30am — No Comments

Amazing Things You Did Not Know You Could Do in Excel

I have included a lot of Excel spreadsheets in the numerous articles and books that I have written in the last 10 years, based either on real life problems or simulations to test algorithms, and featuring various machine learning techniques. It is time to create a new blog series focusing on these useful techniques that can easily be handled with Excel. Data scientists typically use programming languages and other visual tools for these techniques, mostly because they are unaware that it can…

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Added by Vincent Granville on December 16, 2020 at 8:00pm — No Comments

t-SNE : A gem in Data Visualisation

 What is t-SNE?

  • It is a Data Visualization Technique
  • t-SNE stands for t-stochastic neighbor embedding 
  • Developed by Laurens van der Maaten and Geoffrey Hinton in 2008.
  • It is a variation to SNE (Stochastic Neighbor Embedding - Hinton and Roweis,…
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Added by Satyam Rastogi on December 9, 2020 at 12:30am — No Comments

New Tests of Randomness and Independence for Sequences of Observations

There is no statistical test that assesses whether a sequence of observations, time series, or residuals in a regression model, exhibits independence or not. Typically, what data scientists do is to look at auto-correlations and see whether they are close enough to zero. If the data follows a Gaussian distribution, then absence of auto-correlations implies independence. Here however, we are dealing with non-Gaussian observations. The setting is similar to testing whether a pseudo-random…

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Added by Vincent Granville on December 2, 2020 at 4:30pm — No Comments

Network Graph Visualizations with DOT

Network graphs play a large part in both computing and data science, and they are essential for working with (and visualizing) both semantic graphs and property graphs. Nearly thirty years ago, AT&T produced a set of libraries called graphviz which were…

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Added by Kurt A Cagle on November 29, 2020 at 2:00pm — No Comments

Probability Mass Function vs Probability Density Function vs Cumulative Density Function (In One Picture)

  • This one picture shows how the CDF compares with the PDF and PMF.
  • All can be used to calculate probabilities.
  • Each function has a unique purpose.
  • The Cumulative Density Function (CDF) is the easiest to understand [1].

References:…

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Added by Stephanie Glen on November 10, 2020 at 4:54am — No Comments

AI Generated Avatars Becoming Digital Influencers

As the recent rise in Covid-19 threatens once again to shutter advertising agencies, film studios, and similar media "factories" globally, a quiet, desperate shift is taking place in the creation of new media, brought about by increasingly sophisticated AI capabilities. A new spate of actors and models are making their way to people's screens, such as…

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Added by Kurt A Cagle on November 2, 2020 at 9:00pm — No Comments

Visualizing New York City WiFi Access with K-Means Clustering

Visualization has become a key application of data science in the telecommunications industry.

Specifically, telecommunication analysis is highly dependent on the use of geospatial data. This is because telecommunication networks in themselves are geographically dispersed, and analysis of such dispersions can yield valuable insights regarding network…

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Added by Vincent Granville on July 30, 2020 at 11:57am — No Comments

Model Selection: Adjusted Coefficient of Determination-Variance Tradeoff

In my previous article, we analyzed the COVID-19 data of Turkey and selected the cubic model for predicting the spread of disease. In this article, we will show in detail why we selected the cubic model for prediction and see whether our decision was right or not.

When we analyze the regression trend models we should consider overfitting and underfitting…

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Added by Selcuk Disci on July 10, 2020 at 2:30am — No Comments

Fourier Series and Differential Equations with some applications in R and Python (Part 2)

This is the 2nd part of the article on a few applications of Fourier Series in solving differential equations. All the problems are taken from the edx Course: MITx - 18.03Fx: Differential Equations Fourier Series and Partial Differential Equations. The article…

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Added by Sandipan Dey on July 4, 2020 at 5:00pm — No Comments

Fourier Series and Differential Equations with some applications in R (Part 1)

In this article, a few applications of Fourier Series in solving differential equations will be described. All the problems are taken from the edx Course: MITx - 18.03Fx: Differential Equations Fourier Series and Partial Differential Equations. The article will be posted in two parts (two separate blongs)

First a basic introduction to the Fourier series will be given and then we shall see how to solve the following ODEs / PDEs using Fourier series:

  1. Find…
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Added by Sandipan Dey on July 4, 2020 at 5:00pm — 3 Comments

Using Neural Networks to Predict Cimate Change, Droughts, and Conflict Displacements

The Problem

Millions of people are forced to leave their current area of residence or community due to resource shortage and natural disasters such as droughts, floods. Our project partner, UNHCR, provides assistance and protection for those who are forcibly displaced inside Somalia.

The goal of this project was to create a solution that quantifies…

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Added by Omdena Community Members on June 25, 2020 at 3:30am — No Comments

Generative Adversarial Networks (GANs) & Bayesian Networks

gan-asian Generative Adversarial Networks (GANs) software is software for producing forgeries and imitations of data (aka synthetic data, fake data). Human beings have been making fakes, with good or evil intent, of almost everything they possibly can, since the beginning of the human race. Thus, perhaps not too surprisingly, GAN software has been widely used since it was first proposed in this amazingly recent 2014 paper. To gauge how widely GAN software has been used so far, see, for…

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Added by Robert R. Tucci on June 24, 2020 at 11:30pm — No Comments

Introduction to Gradient Decent

The gradient decent approach is used in many algorithms to minimize loss functions. In this introduction we will see how exactly a gradient descent works. In addition, some special features will be pointed out. We will be guided by a practical example.…

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Added by Frank Raulf on June 24, 2020 at 7:00am — No Comments

Stunning 3D visualization with JavaView

JavaView(http://www.javaview.de/) is a 3D geometry viewer and a mathematical visualization software known since 90x. The program is written in Java, and enables a smooth integration into commercial…

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Added by jwork.ORG on June 21, 2020 at 5:30pm — No Comments

Simple Correlational Analysis on Socioeconomic Factors Impacting Covid-19 Outbreak in US Counties

Background

As part of my PhD work, I recently had to analyze any dataset(s) of my interest and present findings.  I ended up conducting a study on US County-wise Covid-19 data.  I wanted to share my key findings through this blog.

Study Question

The primary question I wanted to address through data analysis was “Do counties’ socioeconomic factors such as population size, poverty rate, unemployment rate, education percent and…

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Added by Murali Kashaboina on June 20, 2020 at 3:16pm — 2 Comments

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