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Weekly Digest, July 13

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this…

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Added by Vincent Granville on July 12, 2020 at 12:00pm — No Comments

Fourier Series and Differential Equations with some applications in R and Python

Heat / Diffusion Equation

f15 f17

The following animation shows how the temperature changes on the bar with time (considering only the first 100 terms for the Fourier series for the square wave).…

heat3

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Added by Sandipan Dey on July 12, 2020 at 10:00am — No Comments

Traditional vs Deep Learning Algorithms used in BlockChain in Retail Industry

Use of SecureSVM, Boosting, Bagging, Clustering, LSTM, CNN, GAN in Retail with BlockChain

Introduction

This blog highlights different ML algorithms used in blockchain transactions with a special emphasis on bitcoins in retail payments. This blog is structured as follows:

  • Overview of the role of blockchain in the retail industry.
  • Different traditional…
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Added by Sharmistha Chatterjee on July 12, 2020 at 5:26am — No Comments

Three fallacies about Covid-19

It is surprising to see the level of innumeracy in the population, even in college-educated professionals. People still have blind faith in so-called experts and journalists, many experts being innumerate themselves when it comes to reading and interpreting data, even if they are experts in their own field. Here I discuss three examples.…

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Added by Vincent Granville on July 11, 2020 at 10:00am — 1 Comment

Overcoming an Imbalanced Dataset using Oversampling.

How oversampling yielded great…

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Added by Michael Burkhardt on July 10, 2020 at 3:49am — 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 2:55am — No Comments

Simpson’s Paradox, the Bane of Clinical Trials

(This article is now a chapter of my github proto-book Bayesuvius)

Simpson's paradox is a recurring nightmare for all statisticians overseeing a clinical trial for a medicine. It is possible that if they leave out a certain "confounding" variable from a study, the study's conclusion on whether a medicine is effective or not, might be, without measuring that confounding variable, the opposite of what it would have been had that variable…

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Added by Robert R. Tucci on July 9, 2020 at 7:00pm — No Comments

Thursday News, July 9

Here is our selection of featured articles and technical resources posted since Monday:

Announcements

Resources…

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Added by Vincent Granville on July 9, 2020 at 12:30pm — No Comments

Blockdrop to Accelerate Neural Network training by IBM Research

Scaling AI with Dynamic Inference Paths in Neural Networks

Introduction

IBM Research, with the help of the University of Texas Austin and the University of Maryland, has created a technology, called BlockDrop, that promises to speed convolutional neural network operations without any loss of fidelity.

This could further excel the use of neural nets, particularly in places with limited computing capability.

Increase in accuracy…

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Added by Sharmistha Chatterjee on July 9, 2020 at 12:00pm — No Comments

Difference Between Correlation and Regression in Statistics

Correlation is a measure of linear association between two variables X and Y, while linear regression is a technique to make predictions, using the following model:

Y = a0a1 X1 + ...…

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Added by Vincent Granville on July 9, 2020 at 6:00am — 1 Comment

Data Decay and Data Enrichment

Data, an organization’s intellectual asset, must be treated and regularly enriched to remain useful and valuable. Over 80% of companies we’ve worked with, — including Fortune 500 organizations — recorded up to 50% growth in sales and customer satisfaction as one of the many benefits of data enrichment. Those that enriched data in line with a company-wide data management plan recorded a 2X increase in ROI.

In this…

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Added by Farah Kim on July 8, 2020 at 8:00pm — No Comments

How to Communicate Data

The following graphic is based on Sam Priddy's excellent DSC/Tableau Webinar How to Accelerate and Scale Your Data Science Workflows. Sam covered many interesting points for organizing, analyzing and presenting data--including which graph is best suited for different data types. This graphic is an overview of some of Sam's points. For more…

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Added by Stephanie Glen on July 8, 2020 at 9:02am — No Comments

Added Chapter on Reinforcement Learning to my book “Bayesuvius” on Bayesian Networks

I just uploaded a new chapter to my github proto-book "Bayesuvius". This chapter deals with Reinforcement Learning (RL) done right, i.e., with Bayesian Networks :)

My chapter is heavily based on the excellent course notes for CS 285 taught at UC Berkeley by Prof. Sergey Levine. All I did was to translate some of those lectures into B net lingo.

During a recent conversation that I had on LinkedIn with some very smart Machine Learning experts, the experts opined that the fields…

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Added by Robert R. Tucci on July 7, 2020 at 12:00pm — No Comments

Why Data Science is a hot Career in 2020

 Data scientist ranks third on the list of LinkedIn emerging jobs of 2020. Similarly, it ranks first on Glassdoor’s hottest jobs of 2020. The data scientist role has been consistently ranked among top jobs in the past few years. There’s not a slightest of doubt that data scientists are in huge demand and are expected to stay in high demand in the coming years. …



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Added by Aileen Scott on July 6, 2020 at 3:00am — No Comments

Building a Deep-Learning-Based Movie Recommender System

With the continuous development of network technology and the ever-expanding scale of e-commerce, the number and variety of goods grow rapidly and users need to spend a lot of time to find the goods they want to buy. This is information overload. To solve this problem, the recommendation system came into being.

The recommendation system is a…

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Added by Kate Shao on July 5, 2020 at 11:30pm — No Comments

Weekly Digest, July 6

Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.  …

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Added by Vincent Granville on July 5, 2020 at 6:00pm — 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

Data As Commodity: For Data Science Professional

What is a commodity?

Commodity are basic raw materials with certain standards that are used with other goods, commodity are often the basis of the production of various finished goods or services and then referred to as commodities (something made based on commodity). Some examples of commodity are seen from their types: metal (gold, silver, platinum, and copper); energy (crude oil and natural gas); livestock and agriculture (beef, mutton, rice, wheat, corn, soybeans,…

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Added by Jeefri A. Moka on July 3, 2020 at 6:30pm — No Comments

Data Governance: Bottom Up Approach to break silos

Over a period, large organizations have been transformed into disintegrated silos that has grown to be a major impediment to respond to changing market demands with agility. Organizational silos have led to innumerous disconnected policies, systems, processes, standards, teams. In order to sustain in this digital era, it’s imperative for organizations to take a top down enterprise value chain view to continually evaluate its ability to adapt (as well as compete) to changing market…

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Added by Subin George on July 3, 2020 at 3:40am — No Comments

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