Time Series forecasting in PBI is based on the thumb technique of smoothening time series prediction called Exponential Smoothening (ES). ES of time series data assigns exponentially decreasing weights for newest to oldest observations. ES is also be used for time series with trend and seasonality. This model is usually used to make short term forecasts, as longer-term forecasts using this technique can be quite unreliable. Collectively, the methods are sometimes referred to as ETS models,…Continue
Added by Vigneswaran S on July 19, 2020 at 1:01am — No Comments
I have been reading a book recently about algorithms in the wider sense
(40 algorithms every programmer should know -book and github link below)
I spend a lot of time with algorithms considering my teaching (AI at University of Oxford).
For Machine Learning and Deep Learning, we need to study a…Continue
Added by ajit jaokar on July 16, 2020 at 3:30am — No Comments
If you scour the internet for "ANOVA vs Regression", you might be confused by the results. Are they the same? Or aren't they? The answer is that they can be the same procedure, if you set them up to be that way. But there are differences between the two methods. This one picture sums up those differences.
Added by Stephanie Glen on July 15, 2020 at 12:13pm — No Comments
Venn diagram showing overlap between "quantum" and "neural network"
The term "quantum neural networks" is being used with increasing frequency by the quantum computing community. Maybe as a dishonest, bait-and-switch advertising strategy, this makes sense. However, from a scientific standpoint, "quantum neural network" is a very poor name choice for what is being alluded to here.
Artificial Neural Networks, often called "Neural Nets" for short, are supposed to…Continue
Added by Robert R. Tucci on July 15, 2020 at 4:30am — No Comments
I want to share with you my article about marketplaces. If you are interested in creating one or want to improve your existing marketplace you might be interested in this information. I worked with SPD Group experts to give you the latest information on the subject!
To get the most revenue out of your effort, it is important to pick…Continue
Added by Roman Chuprina on July 14, 2020 at 6:00am — No Comments
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
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
Information catalogs and business glossaries are popular solutions in the data management toolbox. What is the purpose of each and how do they work to effectively manage an organization’s data? Which one should you choose as part of your data management strategy?
What’s in a name?
In the world of data management, business glossaries and information catalogs are sometimes discussed as similar entities and considered interchangeable. However,…Continue
Added by Kim Kaluba on July 10, 2020 at 5:09am — No Comments
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…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
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
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
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
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