Added by Vincent Granville on July 12, 2020 at 12:00pm — No Comments
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).…
Added by Sandipan Dey on July 12, 2020 at 10:00am — No Comments
Use of SecureSVM, Boosting, Bagging, Clustering, LSTM, CNN, GAN in Retail with BlockChain
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:
Added by Sharmistha Chatterjee on July 12, 2020 at 5:00am — No Comments
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.…Continue
How oversampling yielded great…
Added by Michael Burkhardt on July 10, 2020 at 3:30am — No Comments
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 situations; underfitting indicates high bias and low variance while overfitting indicates…Continue
Added by Selcuk Disci on July 10, 2020 at 2:30am — No Comments
(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 been measured. Statisticians have to enlist expert…
Added by Robert R. Tucci on July 9, 2020 at 7:00pm — No Comments
Here is our selection of featured articles and technical resources posted since Monday:
Added by Vincent Granville on July 9, 2020 at 12:30pm — No Comments
Scaling AI with Dynamic Inference Paths in Neural Networks
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…Continue
Added by Sharmistha Chatterjee on July 9, 2020 at 12:00pm — No Comments
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 = a0 + a1 X1 + ...…Continue
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.
Added by Farah Kim on July 8, 2020 at 8:00pm — No Comments
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…Continue
Added by Stephanie Glen on July 8, 2020 at 9:02am — No Comments
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…Continue
Added by Robert R. Tucci on July 7, 2020 at 12:00pm — No Comments
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. …
Added by Aileen Scott on July 6, 2020 at 3:00am — No Comments
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…Continue
Added by Kate Shao on July 5, 2020 at 11:30pm — No Comments
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. …Continue
Added by Vincent Granville on July 5, 2020 at 6:00pm — No Comments
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…
Added by Sandipan Dey on July 4, 2020 at 5:00pm — No Comments
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:
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,…Continue
Added by Jeefri A. Moka on July 3, 2020 at 6:30pm — No Comments
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…Continue
Added by Subin George on July 3, 2020 at 3:40am — No Comments