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,…

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…

Yahoo Finance (below) is a website that gives us a good deal of information about the financial market, including information about stock trading.

To get the numbers for a specific stock, all you have to do is to search for its Yahoo code (ex: VALE - see figure below). This is not necessarily the company’s…

Recently Springer made some good books on maths free to download.

Competitive programming strategies are useful for many data science interviews and they help to improve your maths foundations.  There are not many books on this subject (although there are many good websites and YouTube resources).

So, I hope you find this book…

I dropped out of university as a literature major in the 1980s.  (I needed time to find myself.)  Before I left, I read The Histories by the ancient Greek historian Herodotus.  I decided to name my new data object the Herodotus Event Data Object or HEDO.  A number of HEDOs can be stitched together to form codified narrative.  Those who follow my blogs might recall that I previously developed a system of codified narrative called BERLIN.  HEDOs represent my reinvention of BERLIN.  I…

In this article, I am going to show how to write python code that predicts the price of stock using Machine Learning technique that Long Short-Term Memory (LSTM).

Algorithm Selection

LSTM could not process a single…

Have you heard about AI learning to play computer games on their own and giving tough competitions to expert Human gamers?

A very popular example being Deepmind whose AlphaGo program defeated the South Korean Go world champion in 2016. Other than this there are other AI agents developed with the intent of playing Atari games like…

Summary: This blog is part II of a series showcasing management and analytics of the daily U.S. Covid-19 case/death data published by the Center for Systems Science and Engineering at Johns…

This article is chunk from one of my blog posts on Arima time series forecasting with Python It is a pretty extensive tutorial and until and unless you are not really interested in learning in and outs of about ARIMA time series forecasting don't bother to click. 

But I do wanted to share this list of 5 very useful metrics for a…

Product of two large primes are at the core of many encryption algorithms, as factoring the product is very hard for numbers with a few hundred digits. The two prime factors are associated with the encryption keys (public and private keys). Here we describe a new approach to factoring a big number that is the product of two primes of roughly the same size. It is designed especially to handle this problem and identify flaws in encryption algorithms.  

While at first glance it appears…

Brian Huge and I just posted a working paper following six months of…

The Entropy is one of the most important concepts in many fields like physics, mathematics, information theory, etc.

Entropy is related to the number of states that one stochastic system can take and how this system will evolve with time, in such a way that the uncertainty will be maximized.

This will happened y two ways, first, every system will choose the configuration with a higher degree of entropy among all that are available and second, if we let the system evolve, after…

This article was written by Lixun Zhang.

As a data scientist, I have experience with R. Naturally, when I was first exposed to Microsoft R Open (MRO, formerly Revolution R Open) and Microsoft R Server (MRS, formerly Revolution R Enterprise), I wanted to know the answers for 3 questions:

• What do R, MRO, and MRS…

Web scraping, also known as web harvesting and  web data extraction, basically refers to collecting data from websites via the Hypertext Transfer Protocol (HTTP) or through web browsers. 

How does web scraping work?

Generally, web scraping involves three steps: 

• first, we send a GET request to the server and we will receive a response in a form of web…